Change directory structure

code/utils/conversions.py

@@ -0,0 +1,42 @@
+def convert_to_yolo(bbox, width, height):
+    modified = bbox.copy()
+    modified['xmin%'] = round(bbox['xmin'] / width * 100, 2)
+    modified['ymin%'] = round(bbox['ymin'] / height * 100, 2)
+    modified['width%'] = round((bbox['xmax'] - bbox['xmin']) / width * 100, 2)
+    modified['height%'] = round((bbox['ymax'] - bbox['ymin']) / height * 100,
+                                2)
+    return modified
+
+
+def scale_bboxes(bboxes, resized_hw, original_hw):
+    """Scale bounding boxes from a padded and resized image to fit on
+    original image.
+
+    :param xyxy_boxes Tensor[N, 4]: tensor of xmin, ymin, xmax, ymax
+        per bounding box
+    :param resized_hw Tuple: height and width of the resized image
+    :param original_hw Tuple: height and width of the original image
+    :returns Tensor[N, 4]: tensor of xmin, ymin, xmax, ymax per
+        bounding box
+    """
+    scaled_boxes = bboxes.clone()
+    scale_ratio = resized_hw[0] / original_hw[0], resized_hw[1] / original_hw[1]
+
+    # Remove padding
+    pad_scale = min(scale_ratio)
+    padding = (resized_hw[1] - original_hw[1] * pad_scale) / 2, (
+        resized_hw[0] - original_hw[0] * pad_scale) / 2
+    scaled_boxes[:, [0, 2]] -= padding[0]  # x padding
+    scaled_boxes[:, [1, 3]] -= padding[1]  # y padding
+    scale_ratio = (pad_scale, pad_scale)
+
+    scaled_boxes[:, [0, 2]] /= scale_ratio[1]
+    scaled_boxes[:, [1, 3]] /= scale_ratio[0]
+
+    # Clip bounding xyxy bounding boxes to image shape (height, width)
+    scaled_boxes[:, 0].clamp_(0, original_hw[1])  # xmin
+    scaled_boxes[:, 1].clamp_(0, original_hw[0])  # ymin
+    scaled_boxes[:, 2].clamp_(0, original_hw[1])  # xmax
+    scaled_boxes[:, 3].clamp_(0, original_hw[0])  # ymax
+
+    return scaled_boxes

code/utils/manipulations.py

@@ -0,0 +1,31 @@
+import cv2
+
+
+def draw_boxes(image, bboxes):
+    img = image.copy()
+    for idx, bbox in enumerate(bboxes):
+        xmin, ymin, xmax, ymax = bbox
+        # Draw bounding box and number on original image
+        img = cv2.rectangle(img, (xmin, ymin), (xmax, ymax), (0, 255, 0), 2)
+        img = cv2.putText(img, str(idx), (xmin + 5, ymin + 25),
+                          cv2.FONT_HERSHEY_SIMPLEX, 0.9, (0, 0, 0), 4,
+                          cv2.LINE_AA)
+        img = cv2.putText(img, str(idx), (xmin + 5, ymin + 25),
+                          cv2.FONT_HERSHEY_SIMPLEX, 0.9, (255, 255, 255), 2,
+                          cv2.LINE_AA)
+    return img
+
+
+def get_cutout(img, xmin, xmax, ymin, ymax):
+    """Cut out a bounding box from an image and transform it for
+    object classification model.
+
+    :param img: opencv2 image object in BGR
+    :param int xmin: start of bounding box on x axis
+    :param int xmax: end of bounding box on x axis
+    :param int ymin: start of bounding box on y axis
+    :param int ymax: end of bounding box on y axis
+    :returns: tensor of cropped image in BGR
+    """
+    cropped_image = img[ymin:ymax, xmin:xmax]
+    return cropped_image