update from upstream

README.md

@@ -22,8 +22,6 @@ Localization (without tracking) can also be achieved with deep learning software
 
 [Check out our paper](https://doi.org/10.7554/eLife.47994) to find out more.
 
-**NOTE:** This software is still in early-release development. *Expect some adventures.*
-
 <p align="center">
 <img src="https://github.com/jgraving/jgraving.github.io/blob/master/files/images/zebra.gif" height="256px">
 <img src="https://github.com/jgraving/jgraving.github.io/blob/master/files/images/locust.gif" height="256px">
@@ -144,17 +142,7 @@ If you use DeepPoseKit for your research please cite [our open-access paper](htt
              url={https://doi.org/10.7554/eLife.47994},
              }
 
-You can also read [our open-access preprint](http://preprint.deepposekit.org):
-
-    @article{graving2019preprint,
-             title={DeepPoseKit, a software toolkit for fast and robust animal pose estimation using deep learning},
-             author={Graving, Jacob M and Chae, Daniel and Naik, Hemal and Li, Liang and Koger, Benjamin and Costelloe, Blair R and Couzin, Iain D},
-             journal={bioRxiv},
-             pages={620245},
-             year={2019},
-             publisher={Cold Spring Harbor Laboratory}
-             url={https://doi.org/10.1101/620245}
-             }
+You can also read [our open-access preprint](http://preprint.deepposekit.org).
 
 If you use the [imgaug package](https://github.com/aleju/imgaug) for data augmentation, please also consider [citing it](https://github.com/aleju/imgaug/blob/master/README.md#citation).
 
@@ -163,7 +151,6 @@ If you [use data](https://github.com/jgraving/DeepPoseKit#i-already-have-annotat
 Please also consider citing the relevant references for the pose estimation model(s) used in your research, which can be found in the documentation (i.e., [`StackedDenseNet`](http://jakegraving.com/DeepPoseKit/html/deepposekit/models/StackedDenseNet.html#references), [`StackedHourglass`](http://jakegraving.com/DeepPoseKit/html/deepposekit/models/StackedHourglass.html#references), [`DeepLabCut`](http://jakegraving.com/DeepPoseKit/html/deepposekit/models/DeepLabCut.html#references), [`LEAP`](http://jakegraving.com/DeepPoseKit/html/deepposekit/models/LEAP.html#references)).
 
 # News
-
 - **October 2019:** Our paper describing DeepPoseKit is published at eLife! (http://paper.deepposekit.org)
 - **September 2019**: 
     - Nature News covers DeepPoseKit: [Deep learning powers a motion-tracking revolution](http://doi.org/10.1038/d41586-019-02942-5)

deepposekit/__init__.py

@@ -28,4 +28,4 @@
 
 
 __doc__ = """ """  # open('README.md').read()
-__version__ = "0.3.5"
+__version__ = "0.3.9"

deepposekit/annotate/gui/Annotator.py

@@ -307,6 +307,11 @@ def _data(self):
             self.skeleton["annotated"] = False
         elif self.key is keys.F:
             self.skeleton["annotated"] = True
+        elif self.key is keys.V:
+            if self.skeleton.loc[self.idx, ["x", "y"]].isnull()[0]:
+                self.skeleton.loc[self.idx, ["x", "y"]] = -1
+            else:
+                self.skeleton.loc[self.idx, ["x", "y"]] = np.nan
         elif self.key in [keys.Q, keys.ESC]:
             self._save()
             print("Saved")

deepposekit/annotate/gui/GUI.py

@@ -324,6 +324,9 @@ def _draw_text(self):
                 else:
                     color = self.colors[self.idx]  # (34, 87, 255)
                     border_color = np.bitwise_not(color)
+                if self.skeleton.loc[self.idx, ["x", "y"]].isnull()[0]:
+                    color = (127, 127, 127)
+
                 # color = (3, 255, 118)
                 thickness = 8
 
@@ -332,8 +335,11 @@ def _draw_text(self):
                     color = (254, 79, 48)
                 else:
                     color = self.colors[idx]  # (34, 87, 255)
+                if self.skeleton.loc[text_idx, ["x", "y"]].isnull()[0]:
+                    color = (127, 127, 127)
                 thickness = 2
                 border_color = (0, 0, 0)
+
 
             text = self.skeleton.loc[text_idx, "name"]
             loc = self.text_locs[(idx + len(self.text_locs) // 4) % len(self.text_locs)]
@@ -447,29 +453,31 @@ def _draw_points(self):
         """
         for idx in self.keypoint_index:
             if idx != self.idx:
-                if np.all(self.skeleton.loc[:, "annotated"]):
-                    color = self.colors[idx]
-                    inv_color = (254, 79, 48)
-                    # inv_color = None
-                else:
-                    # color = (34, 87, 255)
-                    color = self.colors[idx]
-                    inv_color = self.inv_colors[idx]
-                center = self._get_scaled_coords(idx)
-                radius = 5
-                if inv_color is not None:
-                    self._draw_point(center, radius, inv_color, 2)
-                self._draw_point(center, radius, color)
-
-        center = self._get_scaled_coords(self.idx)
-        radius = 8
-        # color = (3, 255, 118)
-        color = self.colors[self.idx]
-        inv_color = self.inv_colors[self.idx]
-        self._draw_point(center, radius, inv_color, 2)
-        self._draw_crosshairs(center, radius + 3, inv_color, 2)
-        self._draw_point(center, radius, color)
-        self._draw_crosshairs(center, radius + 3, color, 1)
+                if not self.skeleton.loc[idx, ["x", "y"]].isnull()[0]:
+                    if np.all(self.skeleton.loc[:, "annotated"]):
+                        color = self.colors[idx]
+                        inv_color = (254, 79, 48)
+                        # inv_color = None
+                    else:
+                        # color = (34, 87, 255)
+                        color = self.colors[idx]
+                        inv_color = self.inv_colors[idx]
+                    center = self._get_scaled_coords(idx)
+                    radius = 5
+                    if inv_color is not None:
+                        self._draw_point(center, radius, inv_color, 2)
+                    self._draw_point(center, radius, color)
+
+        if not self.skeleton.loc[self.idx, ["x", "y"]].isnull()[0]:
+            center = self._get_scaled_coords(self.idx)
+            radius = 8
+            # color = (3, 255, 118)
+            color = self.colors[self.idx]
+            inv_color = self.inv_colors[self.idx]
+            self._draw_point(center, radius, inv_color, 2)
+            self._draw_crosshairs(center, radius + 3, inv_color, 2)
+            self._draw_point(center, radius, color)
+            self._draw_crosshairs(center, radius + 3, color, 1)
 
     def _draw_lines(self):
         """ Draw lines
@@ -483,7 +491,9 @@ def _draw_lines(self):
             color = (34, 87, 255)
         for idx in self.keypoint_index:
             tree = self.skeleton.loc[idx, "tree"]
-            if tree >= 0:
+            if (tree >= 0 and
+                not self.skeleton.loc[tree, ["x", "y"]].isnull()[0] and
+                not self.skeleton.loc[idx, ["x", "y"]].isnull()[0]):
                 pt1 = self._get_scaled_coords(idx)
                 pt2 = self._get_scaled_coords(tree)
                 cv2.line(

deepposekit/annotate/utils/hotkeys.py

@@ -20,6 +20,8 @@
 A = ord("a")
 S = ord("s")
 D = ord("d")
+V = ord("v")
+
 SPACE = ord(" ")
 
 

deepposekit/io/BaseGenerator.py

@@ -74,7 +74,7 @@ def get_images(self, indexes):
         Takes a list or array of indexes corresponding
         to image-keypoint pairs in the dataset.
         Returns a numpy array of images with the shape:
-        (1, height, width, n_channels)
+        (n_samples, height, width, n_channels)
         """
         raise NotImplementedError()
 
@@ -83,7 +83,7 @@ def get_keypoints(self, indexes):
         Takes a list or array of indexes corresponding to
         image-keypoint pairs in the dataset.
         Returns a numpy array of keypoints with the shape:
-        (1, n_keypoints, 2), where 2 is the x,y coordinates
+        (n_samples, n_keypoints, 2), where 2 is the x,y coordinates
         """
         raise NotImplementedError()
 

deepposekit/io/TrainingGenerator.py

@@ -237,7 +237,7 @@ def __call__(self, n_outputs=1, batch_size=32, validation=False, confidence=True
         self.confidence = confidence
         self.on_epoch_end()
         self_copy = copy.deepcopy(self)
-        if self.augmenter:
+        if self.augmenter is not None:
             self_copy.augmenter.reseed()
         return self_copy
 
@@ -289,7 +289,7 @@ def augment(self, images, keypoints):
     def generate_batch(self, indexes):
         """Generates data containing batch_size samples"""
         X, y = self.load_batch(indexes)
-        if self.augmenter and not self.validation:
+        if self.augmenter is not None and not self.validation:
             X, y = self.augment(X, y)
         if self.confidence:
             y = draw_confidence_maps(
@@ -309,7 +309,7 @@ def generate_batch(self, indexes):
         return X, y
 
     def get_config(self):
-        if self.augmenter:
+        if self.augmenter is not None:
             augmenter = True
         else:
             augmenter = False

deepposekit/io/video.py

@@ -13,7 +13,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from tensorflow.python.keras.utils import Sequence
+from tensorflow.keras.utils import Sequence
 import cv2
 import numpy as np
 import os

deepposekit/models/engine.py

@@ -234,7 +234,7 @@ def save(self, path, overwrite=True):
 
     def get_config(self):
         config = {}
-        if self.train_generator:
+        if self.train_generator is not None:
             base_config = self.train_generator.get_config()
             return dict(list(base_config.items()) + list(config.items()))
         else:

deepposekit/models/layers/convolutional.py

@@ -13,8 +13,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from tensorflow.python.keras.engine import Layer
-from tensorflow.python.keras.engine import InputSpec
+from tensorflow.keras.layers import Layer, InputSpec
 
 from tensorflow.keras.layers import UpSampling2D
 

deepposekit/models/layers/imagenet_densenet.py

@@ -27,12 +27,11 @@
 import numpy as np
 import tensorflow.keras as keras
 
-from tensorflow.python.keras.applications import imagenet_utils
-from tensorflow.python.keras.applications.imagenet_utils import decode_predictions
+from deepposekit.models.layers import imagenet_utils
+from deepposekit.models.layers.imagenet_utils import decode_predictions
 from tensorflow.keras.layers import Layer
-from tensorflow.python.keras.applications import keras_applications
 
-_obtain_input_shape = imagenet_utils.imagenet_utils._obtain_input_shape
+_obtain_input_shape = imagenet_utils._obtain_input_shape
 
 backend = keras.backend
 layers = keras.layers

deepposekit/models/layers/imagenet_mobile.py

@@ -80,14 +80,13 @@
 import numpy as np
 import tensorflow.keras as keras
 
-from tensorflow.python.keras.applications import imagenet_utils
-from tensorflow.python.keras.applications.imagenet_utils import decode_predictions
+from deepposekit.models.layers import imagenet_utils
+from deepposekit.models.layers.imagenet_utils import decode_predictions
 from tensorflow.keras.layers import Layer
-from tensorflow.python.keras.applications import keras_applications
-from tensorflow.python.keras.applications.mobilenet_v2 import preprocess_input
+from tensorflow.keras.applications.mobilenet_v2 import preprocess_input
 
-correct_pad = keras_applications.correct_pad
-_obtain_input_shape = imagenet_utils.imagenet_utils._obtain_input_shape
+correct_pad = imagenet_utils.correct_pad
+_obtain_input_shape = imagenet_utils._obtain_input_shape
 
 
 # TODO Change path to v1.1

deepposekit/models/layers/imagenet_resnet.py

@@ -27,9 +27,9 @@
 import tensorflow.keras as keras
 from tensorflow.keras.layers import Layer
 
-from tensorflow.python.keras.applications import imagenet_utils
+from deepposekit.models.layers import imagenet_utils
 
-_obtain_input_shape = imagenet_utils.imagenet_utils._obtain_input_shape
+_obtain_input_shape = imagenet_utils._obtain_input_shape
 
 backend = keras.backend
 layers = keras.layers