From 23cd4ecfa7a0844ff2fb4bf748ce188458bd774c Mon Sep 17 00:00:00 2001 From: Glenn Jocher Date: Mon, 22 Apr 2019 16:17:01 +0200 Subject: [PATCH] updates --- utils/datasets.py | 31 ++++++++++--------------------- 1 file changed, 10 insertions(+), 21 deletions(-) diff --git a/utils/datasets.py b/utils/datasets.py index 2ebed801..d5cbbc38 100755 --- a/utils/datasets.py +++ b/utils/datasets.py @@ -74,7 +74,7 @@ class LoadImages: # for inference print('image %g/%g %s: ' % (self.count, self.nF, path), end='') # Padded resize - img, _, _, _ = letterbox_rect(img0, height=self.height) + img, _, _, _ = letterbox(img0, height=self.height) print('%gx%g ' % img.shape[:2], end='') # print image size # Normalize RGB @@ -176,7 +176,7 @@ class LoadImagesAndLabels(Dataset): # for training/testing cv2.cvtColor(img_hsv, cv2.COLOR_HSV2BGR, dst=img) h, w, _ = img.shape - img, ratio, padw, padh = letterbox(img, height=self.img_size) + img, ratio, padw, padh = letterbox(img, height=self.img_size, mode='square') # Load labels labels = [] @@ -236,30 +236,19 @@ class LoadImagesAndLabels(Dataset): # for training/testing return torch.stack(img, 0), torch.cat(label, 0), path, hw -def letterbox(img, height=416, color=(127.5, 127.5, 127.5)): - # Resize a rectangular image to a padded square - shape = img.shape[:2] # shape = [height, width] - ratio = float(height) / max(shape) # ratio = old / new - new_shape = (round(shape[1] * ratio), round(shape[0] * ratio)) # new_shape = [width, height] - - dw = (height - new_shape[0]) / 2 # width padding - dh = (height - new_shape[1]) / 2 # height padding - - top, bottom = round(dh - 0.1), round(dh + 0.1) - left, right = round(dw - 0.1), round(dw + 0.1) - img = cv2.resize(img, new_shape, interpolation=cv2.INTER_AREA) # resized, no border - img = cv2.copyMakeBorder(img, top, bottom, left, right, cv2.BORDER_CONSTANT, value=color) # padded square - return img, ratio, dw, dh - - -def letterbox_rect(img, height=416, color=(127.5, 127.5, 127.5)): +def letterbox(img, height=416, color=(127.5, 127.5, 127.5), mode='rect'): # Resize a rectangular image to a 32 pixel multiple rectangle shape = img.shape[:2] # shape = [height, width] ratio = float(height) / max(shape) # ratio = old / new new_shape = (round(shape[1] * ratio), round(shape[0] * ratio)) # new_shape = [width, height] - dw = np.mod(height - new_shape[0], 32) / 2 # width padding - dh = np.mod(height - new_shape[1], 32) / 2 # height padding + # Select padding https://github.com/ultralytics/yolov3/issues/232 + if mode is 'rect': # rectangle + dw = np.mod(height - new_shape[0], 32) / 2 # width padding + dh = np.mod(height - new_shape[1], 32) / 2 # height padding + else: # square + dw = (height - new_shape[0]) / 2 # width padding + dh = (height - new_shape[1]) / 2 # height padding top, bottom = int(round(dh - 0.1)), int(round(dh + 0.1)) left, right = int(round(dw - 0.1)), int(round(dw + 0.1))