diff --git a/ade20k_labels.py b/ade20k_labels.py index 64cd2f4..50fb82d 100644 --- a/ade20k_labels.py +++ b/ade20k_labels.py @@ -166,13 +166,3 @@ Label('flag', 149, (92, 0, 255))] ade20k_id2label = {label.id: label for label in labels} - - -def import_labels_from_mat(): - colors = scipy.io.loadmat('utils/colorization/color150.mat') - object_names = scipy.io.loadmat('utils/colorization/objectName150.mat') - for id in range(150): - color = colors['colors'][id] - name = object_names['objectNames'][id][0][0] - labels.append(Label(name, id, color)) - print("Label(\'%s\', %i, (%i, %i, %i))," % (name, id, color[0], color[1], color[2])) diff --git a/cityscapes_labels.py b/cityscapes_labels.py index 5aeb1c2..ff9113d 100644 --- a/cityscapes_labels.py +++ b/cityscapes_labels.py @@ -150,39 +150,3 @@ def assureSingleInstanceName(name): return None # all good then return name - -# -------------------------------------------------------------------------------- -# Main for testing -# -------------------------------------------------------------------------------- - - -# just a dummy main -if __name__ == "__main__": - # Print all the labels - print("List of cityscapes labels:") - print("") - print(" {:>21} | {:>3} | {:>7} | {:>14} | {:>10} | {:>12} | {:>12}".format( - 'name', 'id', 'trainId', 'category', 'categoryId', 'hasInstances', 'ignoreInEval')) - print(" " + ('-' * 98)) - for label in labels: - print(" {:>21} | {:>3} | {:>7} | {:>14} | {:>10} | {:>12} | {:>12}".format( - label.name, label.id, label.trainId, label.category, label.categoryId, label.hasInstances, label.ignoreInEval)) - print("") - - print("Example usages:") - - # Map from name to label - name = 'car' - id = name2label[name].id - print("ID of label '{name}': {id}".format(name=name, id=id)) - - # Map from ID to label - category = id2label[id].category - print("Category of label with ID '{id}': {category}".format( - id=id, category=category)) - - # Map from trainID to label - trainId = 0 - name = trainId2label[trainId].name - print("Name of label with trainID '{id}': {name}".format( - id=trainId, name=name)) diff --git a/data b/data deleted file mode 120000 index 5d60416..0000000 --- a/data +++ /dev/null @@ -1 +0,0 @@ -/home/avatar/datasets/ \ No newline at end of file diff --git a/drawImage/__init__.py b/drawImage/__init__.py deleted file mode 100644 index 6203fe3..0000000 --- a/drawImage/__init__.py +++ /dev/null @@ -1 +0,0 @@ -from drawModule import * \ No newline at end of file diff --git a/drawImage/__init__.pyc b/drawImage/__init__.pyc deleted file mode 100644 index 80696bb..0000000 Binary files a/drawImage/__init__.pyc and /dev/null differ diff --git a/drawImage/drawModule.py b/drawImage/drawModule.py deleted file mode 100644 index 42d0c6a..0000000 --- a/drawImage/drawModule.py +++ /dev/null @@ -1,75 +0,0 @@ -from PIL import Image, ImageDraw -import scipy.ndimage -import scipy.io -import numpy as np -import time -import copy - - -class BaseDraw: - def __init__(self, color150, objectNames, img, pred_size, predicted_classes): - self.class_colors = scipy.io.loadmat(color150) - self.class_names = scipy.io.loadmat(objectNames, struct_as_record=False) - self.im = img - self.pred_size = pred_size - self.predicted_classes = copy.deepcopy(predicted_classes) - self.original_W = self.im.size[0] - self.original_H = self.im.size[1] - - self.output_W = self.original_W - self.output_H = self.original_H - - - def dumpArray(self, array, i): - test = array*100 - test = Image.fromarray(test.astype('uint8')) - test = test.convert("RGB") - test.save('/home/vlad/oS_AI/'+str(i)+'t.jpg', "JPEG") - - def calculateResize(self): - W_coef = float(self.original_W)/float(self.output_W) - H_coef = float(self.original_H)/float(self.output_H) - horiz_pad = 0 - vert_pad = 0 - if W_coef > H_coef: - coef = W_coef - horiz_pad = int((self.output_H - self.original_H/coef)/2) - return [coef, horiz_pad, vert_pad] - else: - coef = H_coef - vert_pad = int((self.output_W - self.original_W/coef)/2) - return [coef, horiz_pad, vert_pad] - - - def resizeToOutput(self, image, coef, h_pad, w_pad): - image = image.resize((int(self.original_W/coef), int(self.original_H/coef)), resample=Image.BILINEAR) - outputImage = Image.new("RGB",(self.output_W,self.output_H),(0,0,0)) - outputImage.paste(image,(w_pad,h_pad)) - return outputImage - - - - def drawSimpleSegment(self): - - #Drawing module - im_Width, im_Height = self.pred_size - prediction_image = Image.new("RGB", (im_Width, im_Height) ,(0,0,0)) - prediction_imageDraw = ImageDraw.Draw(prediction_image) - - #BASE all image segmentation - for i in range(im_Width): - for j in range(im_Height): - #get matrix element class(0-149) - px_Class = self.predicted_classes[j][i] - #assign color from .mat list - put_Px_Color = tuple(self.class_colors['colors'][px_Class]) - - #drawing - prediction_imageDraw.point((i,j), fill=put_Px_Color) - - #Resize to original size and save - self.coef, self.h_pad, self.w_pad = self.calculateResize() - FullHdOutImage = self.resizeToOutput(prediction_image, self.coef, self.h_pad, self.w_pad) - FullHdOutImage = Image.blend(FullHdOutImage, self.im, 0.5) - - return FullHdOutImage diff --git a/drawImage/drawModule.pyc b/drawImage/drawModule.pyc deleted file mode 100644 index 5a8bc97..0000000 Binary files a/drawImage/drawModule.pyc and /dev/null differ diff --git a/pspnet-video.py b/pspnet-video.py index d231093..69713cf 100644 --- a/pspnet-video.py +++ b/pspnet-video.py @@ -16,7 +16,7 @@ from keras.models import model_from_json import tensorflow as tf import layers_builder as layers -import utils +from utils import utils import matplotlib.pyplot as plt import cv2 import datetime diff --git a/pspnet.py b/pspnet.py index a5fd563..17151ae 100755 --- a/pspnet.py +++ b/pspnet.py @@ -10,7 +10,7 @@ import tensorflow as tf import layers_builder as layers from glob import glob -from python_utils import utils +from utils import utils from keras.utils.generic_utils import CustomObjectScope import cv2 import math diff --git a/train.py b/train.py index 7bb78bb..0b350d8 100644 --- a/train.py +++ b/train.py @@ -1,8 +1,8 @@ from os import path from os.path import join from scipy.misc import imresize -from python_utils.preprocessing import data_generator_s31 -from python_utils.callbacks import callbacks +from utils.preprocessing import data_generator_s31 +from utils.callbacks import callbacks from keras.models import load_model import layers_builder as layers import numpy as np diff --git a/utils.py b/utils.py deleted file mode 100644 index f29c799..0000000 --- a/utils.py +++ /dev/null @@ -1,91 +0,0 @@ -from __future__ import print_function -import colorsys -import numpy as np -from keras.models import Model -from cityscapes_labels import trainId2label -from ade20k_labels import ade20k_id2label -from pascal_voc_labels import voc_id2label - - -def class_image_to_image(class_id_image, class_id_to_rgb_map): - """Map the class image to a rgb-color image.""" - colored_image = np.zeros((class_id_image.shape[0], class_id_image.shape[1], 3), np.uint8) - for i in range(-1,256): - try: - cl = class_id_to_rgb_map[i] - colored_image[class_id_image[:,:]==i] = cl.color - except KeyError as key_error: - pass - return colored_image - - -def class_image_to_image_slow(class_id_image, class_id_to_rgb_map): - """Map the class image to a rgb-color image.""" - colored_image = np.zeros((class_id_image.shape[0], class_id_image.shape[1], 3), np.uint8) - for row in range(class_id_image.shape[0]): - for col in range(class_id_image.shape[1]): - try: - colored_image[row, col, :] = class_id_to_rgb_map[int(class_id_image[row, col])].color - except KeyError as key_error: - print("Warning: could not resolve classid %s" % key_error) - return colored_image - - -def color_class_image(class_image, model_name): - """Color classed depending on the model used.""" - if 'cityscapes' in model_name: - colored_image = class_image_to_image(class_image, trainId2label) - elif 'voc' in model_name: - colored_image = class_image_to_image(class_image, voc_id2label) - elif 'ade20k' in model_name: - colored_image = class_image_to_image(class_image, ade20k_id2label) - else: - colored_image = add_color(class_image) - return colored_image - -def color_class_image_slow(class_image, model_name): - """Color classed depending on the model used.""" - if 'cityscapes' in model_name: - colored_image = class_image_to_image_slow(class_image, trainId2label) - elif 'voc' in model_name: - colored_image = class_image_to_image_slow(class_image, voc_id2label) - elif 'ade20k' in model_name: - colored_image = class_image_to_image_slow(class_image, ade20k_id2label) - else: - colored_image = add_color(class_image) - return colored_image - - -def add_color(img): - """Color classes a good distance away from each other.""" - h, w = img.shape - img_color = np.zeros((h, w, 3)) - for i in xrange(1, 151): - img_color[img == i] = to_color(i) - return img_color * 255 # is [0.0-1.0] should be [0-255] - - -def to_color(category): - """Map each category color a good distance away from each other on the HSV color space.""" - v = (category-1)*(137.5/360) - return colorsys.hsv_to_rgb(v, 1, 1) - - -def debug(model, data): - """Debug model by printing the activations in each layer.""" - names = [layer.name for layer in model.layers] - for name in names[:]: - print_activation(model, name, data) - - -def print_activation(model, layer_name, data): - """Print the activations in each layer.""" - intermediate_layer_model = Model(inputs=model.input, - outputs=model.get_layer(layer_name).output) - io = intermediate_layer_model.predict(data) - print(layer_name, array_to_str(io)) - - -def array_to_str(a): - return "{} {} {} {} {}".format(a.dtype, a.shape, np.min(a), - np.max(a), np.mean(a)) diff --git a/python_utils/__init__.py b/utils/__init__.py similarity index 100% rename from python_utils/__init__.py rename to utils/__init__.py diff --git a/python_utils/callbacks.py b/utils/callbacks.py 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differ diff --git a/utils/model/pspnet.prototxt b/utils/model/pspnet.prototxt deleted file mode 100644 index c57306f..0000000 --- a/utils/model/pspnet.prototxt +++ /dev/null @@ -1,3894 +0,0 @@ -# -input: "data" -input_dim: 1 -input_dim: 3 -input_dim: 473 -input_dim: 473 - -layer { - name: "conv1_1_3x3_s2" - type: "Convolution" - bottom: "data" - top: "conv1_1_3x3_s2" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 64 - pad: 1 - kernel_size: 3 - stride: 2 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv1_1_3x3_s2/bn" - type: "BN" - bottom: "conv1_1_3x3_s2" - top: "conv1_1_3x3_s2" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv1_1_3x3_s2/relu" - type: "ReLU" - bottom: "conv1_1_3x3_s2" - top: "conv1_1_3x3_s2" -} -layer { - name: "conv1_2_3x3" - type: "Convolution" - bottom: "conv1_1_3x3_s2" - top: "conv1_2_3x3" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 64 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv1_2_3x3/bn" - type: "BN" - bottom: "conv1_2_3x3" - top: "conv1_2_3x3" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv1_2_3x3/relu" - type: "ReLU" - bottom: "conv1_2_3x3" - top: "conv1_2_3x3" -} -layer { - name: "conv1_3_3x3" - type: "Convolution" - bottom: "conv1_2_3x3" - top: "conv1_3_3x3" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 128 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv1_3_3x3/bn" - type: "BN" - bottom: "conv1_3_3x3" - top: "conv1_3_3x3" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv1_3_3x3/relu" - type: "ReLU" - bottom: "conv1_3_3x3" - top: "conv1_3_3x3" -} -layer { - name: "pool1_3x3_s2" - type: "Pooling" - bottom: "conv1_3_3x3" - top: "pool1_3x3_s2" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 2 - pad: 1 - } -} -layer { - name: "conv2_1_1x1_reduce" - type: "Convolution" - bottom: "pool1_3x3_s2" - top: "conv2_1_1x1_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 64 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv2_1_1x1_reduce/bn" - type: "BN" - bottom: "conv2_1_1x1_reduce" - top: "conv2_1_1x1_reduce" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv2_1_1x1_reduce/relu" - type: "ReLU" - bottom: "conv2_1_1x1_reduce" - top: "conv2_1_1x1_reduce" -} -layer { - name: "conv2_1_3x3" - type: "Convolution" - bottom: "conv2_1_1x1_reduce" - top: "conv2_1_3x3" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 64 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv2_1_3x3/bn" - type: "BN" - bottom: "conv2_1_3x3" - top: "conv2_1_3x3" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv2_1_3x3/relu" - type: "ReLU" - bottom: "conv2_1_3x3" - top: "conv2_1_3x3" -} -layer { - name: "conv2_1_1x1_increase" - type: "Convolution" - bottom: "conv2_1_3x3" - top: "conv2_1_1x1_increase" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 256 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv2_1_1x1_increase/bn" - type: "BN" - bottom: "conv2_1_1x1_increase" - top: "conv2_1_1x1_increase" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv2_1_1x1_proj" - type: "Convolution" - bottom: "pool1_3x3_s2" - top: "conv2_1_1x1_proj" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 256 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv2_1_1x1_proj/bn" - type: "BN" - bottom: "conv2_1_1x1_proj" - top: "conv2_1_1x1_proj" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv2_1" - type: "Eltwise" - bottom: "conv2_1_1x1_proj" - bottom: "conv2_1_1x1_increase" - top: "conv2_1" - eltwise_param { - operation: SUM - } -} -layer { - name: "conv2_1/relu" - type: "ReLU" - bottom: "conv2_1" - top: "conv2_1" -} -layer { - name: "conv2_2_1x1_reduce" - type: "Convolution" - bottom: "conv2_1" - top: "conv2_2_1x1_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 64 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv2_2_1x1_reduce/bn" - type: "BN" - bottom: "conv2_2_1x1_reduce" - top: "conv2_2_1x1_reduce" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv2_2_1x1_reduce/relu" - type: "ReLU" - bottom: "conv2_2_1x1_reduce" - top: "conv2_2_1x1_reduce" -} -layer { - name: "conv2_2_3x3" - type: "Convolution" - bottom: "conv2_2_1x1_reduce" - top: "conv2_2_3x3" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 64 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv2_2_3x3/bn" - type: "BN" - bottom: "conv2_2_3x3" - top: "conv2_2_3x3" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv2_2_3x3/relu" - type: "ReLU" - bottom: "conv2_2_3x3" - top: "conv2_2_3x3" -} -layer { - name: "conv2_2_1x1_increase" - type: "Convolution" - bottom: "conv2_2_3x3" - top: "conv2_2_1x1_increase" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 256 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv2_2_1x1_increase/bn" - type: "BN" - bottom: "conv2_2_1x1_increase" - top: "conv2_2_1x1_increase" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv2_2" - type: "Eltwise" - bottom: "conv2_1" - bottom: "conv2_2_1x1_increase" - top: "conv2_2" - eltwise_param { - operation: SUM - } -} -layer { - name: "conv2_2/relu" - type: "ReLU" - bottom: "conv2_2" - top: "conv2_2" -} -layer { - name: "conv2_3_1x1_reduce" - type: "Convolution" - bottom: "conv2_2" - top: "conv2_3_1x1_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 64 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv2_3_1x1_reduce/bn" - type: "BN" - bottom: "conv2_3_1x1_reduce" - top: "conv2_3_1x1_reduce" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv2_3_1x1_reduce/relu" - type: "ReLU" - bottom: "conv2_3_1x1_reduce" - top: "conv2_3_1x1_reduce" -} -layer { - name: "conv2_3_3x3" - type: "Convolution" - bottom: "conv2_3_1x1_reduce" - top: "conv2_3_3x3" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 64 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv2_3_3x3/bn" - type: "BN" - bottom: "conv2_3_3x3" - top: "conv2_3_3x3" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv2_3_3x3/relu" - type: "ReLU" - bottom: "conv2_3_3x3" - top: "conv2_3_3x3" -} -layer { - name: "conv2_3_1x1_increase" - type: "Convolution" - bottom: "conv2_3_3x3" - top: "conv2_3_1x1_increase" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 256 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv2_3_1x1_increase/bn" - type: "BN" - bottom: "conv2_3_1x1_increase" - top: "conv2_3_1x1_increase" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv2_3" - type: "Eltwise" - bottom: "conv2_2" - bottom: "conv2_3_1x1_increase" - top: "conv2_3" - eltwise_param { - operation: SUM - } -} -layer { - name: "conv2_3/relu" - type: "ReLU" - bottom: "conv2_3" - top: "conv2_3" -} -layer { - name: "conv3_1_1x1_reduce" - type: "Convolution" - bottom: "conv2_3" - top: "conv3_1_1x1_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 128 - pad: 0 - kernel_size: 1 - stride: 2 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv3_1_1x1_reduce/bn" - type: "BN" - bottom: "conv3_1_1x1_reduce" - top: "conv3_1_1x1_reduce" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv3_1_1x1_reduce/relu" - type: "ReLU" - bottom: "conv3_1_1x1_reduce" - top: "conv3_1_1x1_reduce" -} -layer { - name: "conv3_1_3x3" - type: "Convolution" - bottom: "conv3_1_1x1_reduce" - top: "conv3_1_3x3" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 128 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv3_1_3x3/bn" - type: "BN" - bottom: "conv3_1_3x3" - top: "conv3_1_3x3" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv3_1_3x3/relu" - type: "ReLU" - bottom: "conv3_1_3x3" - top: "conv3_1_3x3" -} -layer { - name: "conv3_1_1x1_increase" - type: "Convolution" - bottom: "conv3_1_3x3" - top: "conv3_1_1x1_increase" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 512 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv3_1_1x1_increase/bn" - type: "BN" - bottom: "conv3_1_1x1_increase" - top: "conv3_1_1x1_increase" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv3_1_1x1_proj" - type: "Convolution" - bottom: "conv2_3" - top: "conv3_1_1x1_proj" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 512 - pad: 0 - kernel_size: 1 - stride: 2 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv3_1_1x1_proj/bn" - type: "BN" - bottom: "conv3_1_1x1_proj" - top: "conv3_1_1x1_proj" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv3_1" - type: "Eltwise" - bottom: "conv3_1_1x1_proj" - bottom: "conv3_1_1x1_increase" - top: "conv3_1" - eltwise_param { - operation: SUM - } -} -layer { - name: "conv3_1/relu" - type: "ReLU" - bottom: "conv3_1" - top: "conv3_1" -} -layer { - name: "conv3_2_1x1_reduce" - type: "Convolution" - bottom: "conv3_1" - top: "conv3_2_1x1_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 128 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv3_2_1x1_reduce/bn" - type: "BN" - bottom: "conv3_2_1x1_reduce" - top: "conv3_2_1x1_reduce" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv3_2_1x1_reduce/relu" - type: "ReLU" - bottom: "conv3_2_1x1_reduce" - top: "conv3_2_1x1_reduce" -} -layer { - name: "conv3_2_3x3" - type: "Convolution" - bottom: "conv3_2_1x1_reduce" - top: "conv3_2_3x3" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 128 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv3_2_3x3/bn" - type: "BN" - bottom: "conv3_2_3x3" - top: "conv3_2_3x3" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv3_2_3x3/relu" - type: "ReLU" - bottom: "conv3_2_3x3" - top: "conv3_2_3x3" -} -layer { - name: "conv3_2_1x1_increase" - type: "Convolution" - bottom: "conv3_2_3x3" - top: "conv3_2_1x1_increase" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 512 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv3_2_1x1_increase/bn" - type: "BN" - bottom: "conv3_2_1x1_increase" - top: "conv3_2_1x1_increase" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv3_2" - type: "Eltwise" - bottom: "conv3_1" - bottom: "conv3_2_1x1_increase" - top: "conv3_2" - eltwise_param { - operation: SUM - } -} -layer { - name: "conv3_2/relu" - type: "ReLU" - bottom: "conv3_2" - top: "conv3_2" -} -layer { - name: "conv3_3_1x1_reduce" - type: "Convolution" - bottom: "conv3_2" - top: "conv3_3_1x1_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 128 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv3_3_1x1_reduce/bn" - type: "BN" - bottom: "conv3_3_1x1_reduce" - top: "conv3_3_1x1_reduce" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv3_3_1x1_reduce/relu" - type: "ReLU" - bottom: "conv3_3_1x1_reduce" - top: "conv3_3_1x1_reduce" -} -layer { - name: "conv3_3_3x3" - type: "Convolution" - bottom: "conv3_3_1x1_reduce" - top: "conv3_3_3x3" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 128 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv3_3_3x3/bn" - type: "BN" - bottom: "conv3_3_3x3" - top: "conv3_3_3x3" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv3_3_3x3/relu" - type: "ReLU" - bottom: "conv3_3_3x3" - top: "conv3_3_3x3" -} -layer { - name: "conv3_3_1x1_increase" - type: "Convolution" - bottom: "conv3_3_3x3" - top: "conv3_3_1x1_increase" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 512 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv3_3_1x1_increase/bn" - type: "BN" - bottom: "conv3_3_1x1_increase" - top: "conv3_3_1x1_increase" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv3_3" - type: "Eltwise" - bottom: "conv3_2" - bottom: "conv3_3_1x1_increase" - top: "conv3_3" - eltwise_param { - operation: SUM - } -} -layer { - name: "conv3_3/relu" - type: "ReLU" - bottom: "conv3_3" - top: "conv3_3" -} -layer { - name: "conv3_4_1x1_reduce" - type: "Convolution" - bottom: "conv3_3" - top: "conv3_4_1x1_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 128 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv3_4_1x1_reduce/bn" - type: "BN" - bottom: "conv3_4_1x1_reduce" - top: "conv3_4_1x1_reduce" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv3_4_1x1_reduce/relu" - type: "ReLU" - bottom: "conv3_4_1x1_reduce" - top: "conv3_4_1x1_reduce" -} -layer { - name: "conv3_4_3x3" - type: "Convolution" - bottom: "conv3_4_1x1_reduce" - top: "conv3_4_3x3" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 128 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv3_4_3x3/bn" - type: "BN" - bottom: "conv3_4_3x3" - top: "conv3_4_3x3" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv3_4_3x3/relu" - type: "ReLU" - bottom: "conv3_4_3x3" - top: "conv3_4_3x3" -} -layer { - name: "conv3_4_1x1_increase" - type: "Convolution" - bottom: "conv3_4_3x3" - top: "conv3_4_1x1_increase" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 512 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv3_4_1x1_increase/bn" - type: "BN" - bottom: "conv3_4_1x1_increase" - top: "conv3_4_1x1_increase" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv3_4" - type: "Eltwise" - bottom: "conv3_3" - bottom: "conv3_4_1x1_increase" - top: "conv3_4" - eltwise_param { - operation: SUM - } -} -layer { - name: "conv3_4/relu" - type: "ReLU" - bottom: "conv3_4" - top: "conv3_4" -} -layer { - name: "conv4_1_1x1_reduce" - type: "Convolution" - bottom: "conv3_4" - top: "conv4_1_1x1_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 256 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv4_1_1x1_reduce/bn" - type: "BN" - bottom: "conv4_1_1x1_reduce" - top: "conv4_1_1x1_reduce" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv4_1_1x1_reduce/relu" - type: "ReLU" - bottom: "conv4_1_1x1_reduce" - top: "conv4_1_1x1_reduce" -} -layer { - name: "conv4_1_3x3" - type: "Convolution" - bottom: "conv4_1_1x1_reduce" - top: "conv4_1_3x3" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 256 - pad: 2 - dilation: 2 - kernel_size: 3 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv4_1_3x3/bn" - type: "BN" - bottom: "conv4_1_3x3" - top: "conv4_1_3x3" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv4_1_3x3/relu" - type: "ReLU" - bottom: "conv4_1_3x3" - top: "conv4_1_3x3" -} -layer { - name: "conv4_1_1x1_increase" - type: "Convolution" - bottom: "conv4_1_3x3" - top: "conv4_1_1x1_increase" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 1024 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv4_1_1x1_increase/bn" - type: "BN" - bottom: "conv4_1_1x1_increase" - top: "conv4_1_1x1_increase" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv4_1_1x1_proj" - type: "Convolution" - bottom: "conv3_4" - top: "conv4_1_1x1_proj" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 1024 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv4_1_1x1_proj/bn" - type: "BN" - bottom: "conv4_1_1x1_proj" - top: "conv4_1_1x1_proj" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv4_1" - type: "Eltwise" - bottom: "conv4_1_1x1_proj" - bottom: "conv4_1_1x1_increase" - top: "conv4_1" - eltwise_param { - operation: SUM - } -} -layer { - name: "conv4_1/relu" - type: "ReLU" - bottom: "conv4_1" - top: "conv4_1" -} -layer { - name: "conv4_2_1x1_reduce" - type: "Convolution" - bottom: "conv4_1" - top: "conv4_2_1x1_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 256 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv4_2_1x1_reduce/bn" - type: "BN" - bottom: "conv4_2_1x1_reduce" - top: "conv4_2_1x1_reduce" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv4_2_1x1_reduce/relu" - type: "ReLU" - bottom: "conv4_2_1x1_reduce" - top: "conv4_2_1x1_reduce" -} -layer { - name: "conv4_2_3x3" - type: "Convolution" - bottom: "conv4_2_1x1_reduce" - top: "conv4_2_3x3" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 256 - pad: 2 - dilation: 2 - kernel_size: 3 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv4_2_3x3/bn" - type: "BN" - bottom: "conv4_2_3x3" - top: "conv4_2_3x3" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv4_2_3x3/relu" - type: "ReLU" - bottom: "conv4_2_3x3" - top: "conv4_2_3x3" -} -layer { - name: "conv4_2_1x1_increase" - type: "Convolution" - bottom: "conv4_2_3x3" - top: "conv4_2_1x1_increase" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 1024 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv4_2_1x1_increase/bn" - type: "BN" - bottom: "conv4_2_1x1_increase" - top: "conv4_2_1x1_increase" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv4_2" - type: "Eltwise" - bottom: "conv4_1" - bottom: "conv4_2_1x1_increase" - top: "conv4_2" - eltwise_param { - operation: SUM - } -} -layer { - name: "conv4_2/relu" - type: "ReLU" - bottom: "conv4_2" - top: "conv4_2" -} -layer { - name: "conv4_3_1x1_reduce" - type: "Convolution" - bottom: "conv4_2" - top: "conv4_3_1x1_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 256 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv4_3_1x1_reduce/bn" - type: "BN" - bottom: "conv4_3_1x1_reduce" - top: "conv4_3_1x1_reduce" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv4_3_1x1_reduce/relu" - type: "ReLU" - bottom: "conv4_3_1x1_reduce" - top: "conv4_3_1x1_reduce" -} -layer { - name: "conv4_3_3x3" - type: "Convolution" - bottom: "conv4_3_1x1_reduce" - top: "conv4_3_3x3" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 256 - pad: 2 - dilation: 2 - kernel_size: 3 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv4_3_3x3/bn" - type: "BN" - bottom: "conv4_3_3x3" - top: "conv4_3_3x3" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv4_3_3x3/relu" - type: "ReLU" - bottom: "conv4_3_3x3" - top: "conv4_3_3x3" -} -layer { - name: "conv4_3_1x1_increase" - type: "Convolution" - bottom: "conv4_3_3x3" - top: "conv4_3_1x1_increase" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 1024 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv4_3_1x1_increase/bn" - type: "BN" - bottom: "conv4_3_1x1_increase" - top: "conv4_3_1x1_increase" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv4_3" - type: "Eltwise" - bottom: "conv4_2" - bottom: "conv4_3_1x1_increase" - top: "conv4_3" - eltwise_param { - operation: SUM - } -} -layer { - name: "conv4_3/relu" - type: "ReLU" - bottom: "conv4_3" - top: "conv4_3" -} -layer { - name: "conv4_4_1x1_reduce" - type: "Convolution" - bottom: "conv4_3" - top: "conv4_4_1x1_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 256 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv4_4_1x1_reduce/bn" - type: "BN" - bottom: "conv4_4_1x1_reduce" - top: "conv4_4_1x1_reduce" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv4_4_1x1_reduce/relu" - type: "ReLU" - bottom: "conv4_4_1x1_reduce" - top: "conv4_4_1x1_reduce" -} -layer { - name: "conv4_4_3x3" - type: "Convolution" - bottom: "conv4_4_1x1_reduce" - top: "conv4_4_3x3" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 256 - pad: 2 - dilation: 2 - kernel_size: 3 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv4_4_3x3/bn" - type: "BN" - bottom: "conv4_4_3x3" - top: "conv4_4_3x3" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv4_4_3x3/relu" - type: "ReLU" - bottom: "conv4_4_3x3" - top: "conv4_4_3x3" -} -layer { - name: "conv4_4_1x1_increase" - type: "Convolution" - bottom: "conv4_4_3x3" - top: "conv4_4_1x1_increase" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 1024 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv4_4_1x1_increase/bn" - type: "BN" - bottom: "conv4_4_1x1_increase" - top: "conv4_4_1x1_increase" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv4_4" - type: "Eltwise" - bottom: "conv4_3" - bottom: "conv4_4_1x1_increase" - top: "conv4_4" - eltwise_param { - operation: SUM - } -} -layer { - name: "conv4_4/relu" - type: "ReLU" - bottom: "conv4_4" - top: "conv4_4" -} -layer { - name: "conv4_5_1x1_reduce" - type: "Convolution" - bottom: "conv4_4" - top: "conv4_5_1x1_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 256 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv4_5_1x1_reduce/bn" - type: "BN" - bottom: "conv4_5_1x1_reduce" - top: "conv4_5_1x1_reduce" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv4_5_1x1_reduce/relu" - type: "ReLU" - bottom: "conv4_5_1x1_reduce" - top: "conv4_5_1x1_reduce" -} -layer { - name: "conv4_5_3x3" - type: "Convolution" - bottom: "conv4_5_1x1_reduce" - top: "conv4_5_3x3" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 256 - pad: 2 - dilation: 2 - kernel_size: 3 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv4_5_3x3/bn" - type: "BN" - bottom: "conv4_5_3x3" - top: "conv4_5_3x3" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv4_5_3x3/relu" - type: "ReLU" - bottom: "conv4_5_3x3" - top: "conv4_5_3x3" -} -layer { - name: "conv4_5_1x1_increase" - type: "Convolution" - bottom: "conv4_5_3x3" - top: "conv4_5_1x1_increase" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 1024 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv4_5_1x1_increase/bn" - type: "BN" - bottom: "conv4_5_1x1_increase" - top: "conv4_5_1x1_increase" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv4_5" - type: "Eltwise" - bottom: "conv4_4" - bottom: "conv4_5_1x1_increase" - top: "conv4_5" - eltwise_param { - operation: SUM - } -} -layer { - name: "conv4_5/relu" - type: "ReLU" - bottom: "conv4_5" - top: "conv4_5" -} -layer { - name: "conv4_6_1x1_reduce" - type: "Convolution" - bottom: "conv4_5" - top: "conv4_6_1x1_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 256 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv4_6_1x1_reduce/bn" - type: "BN" - bottom: "conv4_6_1x1_reduce" - top: "conv4_6_1x1_reduce" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv4_6_1x1_reduce/relu" - type: "ReLU" - bottom: "conv4_6_1x1_reduce" - top: "conv4_6_1x1_reduce" -} -layer { - name: "conv4_6_3x3" - type: "Convolution" - bottom: "conv4_6_1x1_reduce" - top: "conv4_6_3x3" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 256 - pad: 2 - dilation: 2 - kernel_size: 3 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv4_6_3x3/bn" - type: "BN" - bottom: "conv4_6_3x3" - top: "conv4_6_3x3" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv4_6_3x3/relu" - type: "ReLU" - bottom: "conv4_6_3x3" - top: "conv4_6_3x3" -} -layer { - name: "conv4_6_1x1_increase" - type: "Convolution" - bottom: "conv4_6_3x3" - top: "conv4_6_1x1_increase" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 1024 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv4_6_1x1_increase/bn" - type: "BN" - bottom: "conv4_6_1x1_increase" - top: "conv4_6_1x1_increase" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv4_6" - type: "Eltwise" - bottom: "conv4_5" - bottom: "conv4_6_1x1_increase" - top: "conv4_6" - eltwise_param { - operation: SUM - } -} -layer { - name: "conv4_6/relu" - type: "ReLU" - bottom: "conv4_6" - top: "conv4_6" -} -layer { - name: "conv5_1_1x1_reduce" - type: "Convolution" - bottom: "conv4_6" - top: "conv5_1_1x1_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 512 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv5_1_1x1_reduce/bn" - type: "BN" - bottom: "conv5_1_1x1_reduce" - top: "conv5_1_1x1_reduce" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv5_1_1x1_reduce/relu" - type: "ReLU" - bottom: "conv5_1_1x1_reduce" - top: "conv5_1_1x1_reduce" -} -layer { - name: "conv5_1_3x3" - type: "Convolution" - bottom: "conv5_1_1x1_reduce" - top: "conv5_1_3x3" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 512 - pad: 4 - dilation: 4 - kernel_size: 3 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv5_1_3x3/bn" - type: "BN" - bottom: "conv5_1_3x3" - top: "conv5_1_3x3" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv5_1_3x3/relu" - type: "ReLU" - bottom: "conv5_1_3x3" - top: "conv5_1_3x3" -} -layer { - name: "conv5_1_1x1_increase" - type: "Convolution" - bottom: "conv5_1_3x3" - top: "conv5_1_1x1_increase" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 2048 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv5_1_1x1_increase/bn" - type: "BN" - bottom: "conv5_1_1x1_increase" - top: "conv5_1_1x1_increase" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv5_1_1x1_proj" - type: "Convolution" - bottom: "conv4_6" - top: "conv5_1_1x1_proj" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 2048 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv5_1_1x1_proj/bn" - type: "BN" - bottom: "conv5_1_1x1_proj" - top: "conv5_1_1x1_proj" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv5_1" - type: "Eltwise" - bottom: "conv5_1_1x1_proj" - bottom: "conv5_1_1x1_increase" - top: "conv5_1" - eltwise_param { - operation: SUM - } -} -layer { - name: "conv5_1/relu" - type: "ReLU" - bottom: "conv5_1" - top: "conv5_1" -} -layer { - name: "conv5_2_1x1_reduce" - type: "Convolution" - bottom: "conv5_1" - top: "conv5_2_1x1_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 512 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv5_2_1x1_reduce/bn" - type: "BN" - bottom: "conv5_2_1x1_reduce" - top: "conv5_2_1x1_reduce" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv5_2_1x1_reduce/relu" - type: "ReLU" - bottom: "conv5_2_1x1_reduce" - top: "conv5_2_1x1_reduce" -} -layer { - name: "conv5_2_3x3" - type: "Convolution" - bottom: "conv5_2_1x1_reduce" - top: "conv5_2_3x3" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 512 - pad: 4 - dilation: 4 - kernel_size: 3 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv5_2_3x3/bn" - type: "BN" - bottom: "conv5_2_3x3" - top: "conv5_2_3x3" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv5_2_3x3/relu" - type: "ReLU" - bottom: "conv5_2_3x3" - top: "conv5_2_3x3" -} -layer { - name: "conv5_2_1x1_increase" - type: "Convolution" - bottom: "conv5_2_3x3" - top: "conv5_2_1x1_increase" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 2048 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv5_2_1x1_increase/bn" - type: "BN" - bottom: "conv5_2_1x1_increase" - top: "conv5_2_1x1_increase" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv5_2" - type: "Eltwise" - bottom: "conv5_1" - bottom: "conv5_2_1x1_increase" - top: "conv5_2" - eltwise_param { - operation: SUM - } -} -layer { - name: "conv5_2/relu" - type: "ReLU" - bottom: "conv5_2" - top: "conv5_2" -} -layer { - name: "conv5_3_1x1_reduce" - type: "Convolution" - bottom: "conv5_2" - top: "conv5_3_1x1_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 512 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv5_3_1x1_reduce/bn" - type: "BN" - bottom: "conv5_3_1x1_reduce" - top: "conv5_3_1x1_reduce" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv5_3_1x1_reduce/relu" - type: "ReLU" - bottom: "conv5_3_1x1_reduce" - top: "conv5_3_1x1_reduce" -} -layer { - name: "conv5_3_3x3" - type: "Convolution" - bottom: "conv5_3_1x1_reduce" - top: "conv5_3_3x3" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 512 - pad: 4 - dilation: 4 - kernel_size: 3 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv5_3_3x3/bn" - type: "BN" - bottom: "conv5_3_3x3" - top: "conv5_3_3x3" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv5_3_3x3/relu" - type: "ReLU" - bottom: "conv5_3_3x3" - top: "conv5_3_3x3" -} -layer { - name: "conv5_3_1x1_increase" - type: "Convolution" - bottom: "conv5_3_3x3" - top: "conv5_3_1x1_increase" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - num_output: 2048 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv5_3_1x1_increase/bn" - type: "BN" - bottom: "conv5_3_1x1_increase" - top: "conv5_3_1x1_increase" - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 1 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv5_3" - type: "Eltwise" - bottom: "conv5_2" - bottom: "conv5_3_1x1_increase" - top: "conv5_3" - eltwise_param { - operation: SUM - } -} -layer { - name: "conv5_3/relu" - type: "ReLU" - bottom: "conv5_3" - top: "conv5_3" -} -layer { - name: "conv5_3_pool1" - type: "Pooling" - bottom: "conv5_3" - top: "conv5_3_pool1" - pooling_param { - pool: AVE - kernel_size: 60 - stride: 60 - } -} -layer { - name: "conv5_3_pool1_conv" - type: "Convolution" - bottom: "conv5_3_pool1" - top: "conv5_3_pool1_conv" - param { - lr_mult: 10 - decay_mult: 1 - } - convolution_param { - num_output: 512 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv5_3_pool1_conv/bn" - type: "BN" - bottom: "conv5_3_pool1_conv" - top: "conv5_3_pool1_conv" - param { - lr_mult: 10 - decay_mult: 0 - } - param { - lr_mult: 10 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv5_3_pool1_conv/relu" - type: "ReLU" - bottom: "conv5_3_pool1_conv" - top: "conv5_3_pool1_conv" -} -layer { - name: "conv5_3_pool1_interp" - type: "Interp" - bottom: "conv5_3_pool1_conv" - top: "conv5_3_pool1_interp" - interp_param { - height: 60 - width: 60 - } -} -layer { - name: "conv5_3_pool2" - type: "Pooling" - bottom: "conv5_3" - top: "conv5_3_pool2" - pooling_param { - pool: AVE - kernel_size: 30 - stride: 30 - } -} -layer { - name: "conv5_3_pool2_conv" - type: "Convolution" - bottom: "conv5_3_pool2" - top: "conv5_3_pool2_conv" - param { - lr_mult: 10 - decay_mult: 1 - } - convolution_param { - num_output: 512 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv5_3_pool2_conv/bn" - type: "BN" - bottom: "conv5_3_pool2_conv" - top: "conv5_3_pool2_conv" - param { - lr_mult: 10 - decay_mult: 0 - } - param { - lr_mult: 10 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv5_3_pool2_conv/relu" - type: "ReLU" - bottom: "conv5_3_pool2_conv" - top: "conv5_3_pool2_conv" -} -layer { - name: "conv5_3_pool2_interp" - type: "Interp" - bottom: "conv5_3_pool2_conv" - top: "conv5_3_pool2_interp" - interp_param { - height: 60 - width: 60 - } -} -layer { - name: "conv5_3_pool3" - type: "Pooling" - bottom: "conv5_3" - top: "conv5_3_pool3" - pooling_param { - pool: AVE - kernel_size: 20 - stride: 20 - } -} -layer { - name: "conv5_3_pool3_conv" - type: "Convolution" - bottom: "conv5_3_pool3" - top: "conv5_3_pool3_conv" - param { - lr_mult: 10 - decay_mult: 1 - } - convolution_param { - num_output: 512 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv5_3_pool3_conv/bn" - type: "BN" - bottom: "conv5_3_pool3_conv" - top: "conv5_3_pool3_conv" - param { - lr_mult: 10 - decay_mult: 0 - } - param { - lr_mult: 10 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv5_3_pool3_conv/relu" - type: "ReLU" - bottom: "conv5_3_pool3_conv" - top: "conv5_3_pool3_conv" -} -layer { - name: "conv5_3_pool3_interp" - type: "Interp" - bottom: "conv5_3_pool3_conv" - top: "conv5_3_pool3_interp" - interp_param { - height: 60 - width: 60 - } -} -layer { - name: "conv5_3_pool6" - type: "Pooling" - bottom: "conv5_3" - top: "conv5_3_pool6" - pooling_param { - pool: AVE - kernel_size: 10 - stride: 10 - } -} -layer { - name: "conv5_3_pool6_conv" - type: "Convolution" - bottom: "conv5_3_pool6" - top: "conv5_3_pool6_conv" - param { - lr_mult: 10 - decay_mult: 1 - } - convolution_param { - num_output: 512 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv5_3_pool6_conv/bn" - type: "BN" - bottom: "conv5_3_pool6_conv" - top: "conv5_3_pool6_conv" - param { - lr_mult: 10 - decay_mult: 0 - } - param { - lr_mult: 10 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv5_3_pool6_conv/relu" - type: "ReLU" - bottom: "conv5_3_pool6_conv" - top: "conv5_3_pool6_conv" -} -layer { - name: "conv5_3_pool6_interp" - type: "Interp" - bottom: "conv5_3_pool6_conv" - top: "conv5_3_pool6_interp" - interp_param { - height: 60 - width: 60 - } -} -layer { - name: "conv5_3_concat" - type: "Concat" - bottom: "conv5_3" - bottom: "conv5_3_pool6_interp" - bottom: "conv5_3_pool3_interp" - bottom: "conv5_3_pool2_interp" - bottom: "conv5_3_pool1_interp" - top: "conv5_3_concat" -} -layer { - name: "conv5_4" - type: "Convolution" - bottom: "conv5_3_concat" - top: "conv5_4" - param { - lr_mult: 10 - decay_mult: 1 - } - convolution_param { - num_output: 512 - kernel_size: 3 - stride: 1 - pad: 1 - weight_filler { - type: "msra" - } - bias_term: false - } -} -layer { - name: "conv5_4/bn" - type: "BN" - bottom: "conv5_4" - top: "conv5_4" - param { - lr_mult: 10 - decay_mult: 0 - } - param { - lr_mult: 10 - decay_mult: 0 - } - param { - lr_mult: 0 - decay_mult: 1 - } - param { - lr_mult: 0 - decay_mult: 0 - } - bn_param { - slope_filler { - type: "constant" - value: 1 - } - bias_filler { - type: "constant" - value: 0 - } - frozen: true - momentum: 0.95 - } -} -layer { - name: "conv5_4/relu" - type: "ReLU" - bottom: "conv5_4" - top: "conv5_4" -} -layer { - name: "conv5_4/dropout" - type: "Dropout" - bottom: "conv5_4" - top: "conv5_4" - dropout_param { - dropout_ratio: 0.1 - } -} -layer { - name: "conv6" - type: "Convolution" - bottom: "conv5_4" - top: "conv6" - param { - lr_mult: 10 - decay_mult: 1 - } - param { - lr_mult: 20 - decay_mult: 1 - } - convolution_param { - num_output: 150 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - } -} -layer { - name: "conv6_interp" - type: "Interp" - bottom: "conv6" - top: "conv6_interp" - interp_param { - zoom_factor: 8 - } -} diff --git a/python_utils/preprocessing.py b/utils/preprocessing.py similarity index 100% rename from python_utils/preprocessing.py rename to utils/preprocessing.py diff --git a/python_utils/utils.py b/utils/utils.py similarity index 100% rename from python_utils/utils.py rename to utils/utils.py