adds classification model

Author: robmarkcole

helpers.py

@@ -1,5 +1,7 @@
-from PIL import ImageDraw
-from typing import Tuple
+"""
+Helper utilities.
+"""
+
 
 def read_coco_labels(file_path):
     """
@@ -12,40 +14,3 @@ def read_coco_labels(file_path):
             pair = line.strip().split(maxsplit=1)
             ret[int(pair[0])] = pair[1].strip()
     return ret
-
-def draw_box(
-    draw: ImageDraw,
-    box: Tuple[float, float, float, float],
-    img_width: int,
-    img_height: int,
-    text: str = "",
-    color: Tuple[int, int, int] = (255, 255, 0),
-) -> None:
-    """
-    Draw a bounding box on and image.
-    The bounding box is defined by the tuple (y_min, x_min, y_max, x_max)
-    where the coordinates are floats in the range [0.0, 1.0] and
-    relative to the width and height of the image.
-    For example, if an image is 100 x 200 pixels (height x width) and the bounding
-    box is `(0.1, 0.2, 0.5, 0.9)`, the upper-left and bottom-right coordinates of
-    the bounding box will be `(40, 10)` to `(180, 50)` (in (x,y) coordinates).
-    """
-
-    line_width = 3
-    font_height = 8
-    y_min, x_min, y_max, x_max = box
-    (left, right, top, bottom) = (
-        x_min * img_width,
-        x_max * img_width,
-        y_min * img_height,
-        y_max * img_height,
-    )
-    draw.line(
-        [(left, top), (left, bottom), (right, bottom), (right, top), (left, top)],
-        width=line_width,
-        fill=color,
-    )
-    if text:
-        draw.text(
-            (left + line_width, abs(top - line_width - font_height)), text, fill=color
-        )

models/classification/dogs-vs-cats/README.md

@@ -0,0 +1,5 @@
+## dogs vs cats
+* Custom model trained on [teachable machine image classification](https://teachablemachine.withgoogle.com/train/image)
+* Dataset: 30 cat and 30 dog images from [kaggle dogs vs cats](https://www.kaggle.com/c/dogs-vs-cats)
+* Input size: TBC
+* Type: tensorflow lite quantized

models/classification/dogs-vs-cats/labels.txt

@@ -0,0 +1,2 @@
+0 dog
+1 cat