Merge pull request #100 from serengil/feat-task-1604-validate-project…

…ed-coordinates

confirm projected coordinates are in boundaries

retinaface/RetinaFace.py

@@ -283,7 +283,7 @@ def extract_faces(
 
  # find new facial area coordinates after alignment
  rotated_x1, rotated_y1, rotated_x2, rotated_y2 = postprocess.rotate_facial_area(
- (x, y, x + w, y + h), rotate_angle, rotate_direction, img.shape
+ (x, y, x + w, y + h), rotate_angle, rotate_direction, (img.shape[0], img.shape[1])
  )
  facial_img = aligned_img[
  int(rotated_y1) : int(rotated_y2), int(rotated_x1) : int(rotated_x2)

retinaface/commons/postprocess.py

@@ -114,25 +114,33 @@ def rotate_facial_area(
  # Angle in radians
  angle = angle * np.pi / 180
 
+ height, weight = size
+
  # Translate the facial area to the center of the image
- x = (facial_area[0] + facial_area[2]) / 2 - size[1] / 2
- y = (facial_area[1] + facial_area[3]) / 2 - size[0] / 2
+ x = (facial_area[0] + facial_area[2]) / 2 - weight / 2
+ y = (facial_area[1] + facial_area[3]) / 2 - height / 2
 
  # Rotate the facial area
  x_new = x * np.cos(angle) + y * direction * np.sin(angle)
  y_new = -x * direction * np.sin(angle) + y * np.cos(angle)
 
  # Translate the facial area back to the original position
- x_new = x_new + size[1] / 2
- y_new = y_new + size[0] / 2
+ x_new = x_new + weight / 2
+ y_new = y_new + height / 2
 
- # Calculate the new facial area
+ # Calculate projected coordinates after alignment
  x1 = x_new - (facial_area[2] - facial_area[0]) / 2
  y1 = y_new - (facial_area[3] - facial_area[1]) / 2
  x2 = x_new + (facial_area[2] - facial_area[0]) / 2
  y2 = y_new + (facial_area[3] - facial_area[1]) / 2
 
- return (int(x1), int(y1), int(x2), int(y2))
+ # validate projected coordinates are in image's boundaries
+ x1 = max(int(x1), 0)
+ y1 = max(int(y1), 0)
+ x2 = min(int(x2), weight)
+ y2 = min(int(y2), height)
+
+ return (x1, y1, x2, y2)
 
 
 def bbox_pred(boxes, box_deltas):