From ebd682b25ce6861f694c2930da84cca0720a8b63 Mon Sep 17 00:00:00 2001 From: Glenn Jocher Date: Mon, 11 Feb 2019 12:40:14 +0100 Subject: [PATCH] updates --- utils/datasets.py | 15 +++++++-------- 1 file changed, 7 insertions(+), 8 deletions(-) diff --git a/utils/datasets.py b/utils/datasets.py index 65b03f80..95e86fcd 100755 --- a/utils/datasets.py +++ b/utils/datasets.py @@ -24,7 +24,7 @@ class load_images(): # for inference self.nF = len(self.files) # number of image files self.height = img_size - assert self.nF > 0, 'No images found in path %s' % path + assert self.nF > 0, 'No images found in ' + path def __iter__(self): self.count = -1 @@ -41,7 +41,7 @@ class load_images(): # for inference assert img0 is not None, 'Failed to load ' + img_path # Padded resize - img, ratio, padw, padh = letterbox(img0, height=self.height, color=(127.5, 127.5, 127.5)) + img, _, _, _ = letterbox(img0, height=self.height) # Normalize RGB img = img[:, :, ::-1].transpose(2, 0, 1) @@ -58,13 +58,12 @@ class load_images(): # for inference class load_images_and_labels(): # for training def __init__(self, path, batch_size=1, img_size=608, multi_scale=False, augment=False): self.path = path - # self.img_files = sorted(glob.glob('%s/*.*' % path)) with open(path, 'r') as file: self.img_files = file.readlines() self.img_files = [path.replace('\n', '') for path in self.img_files] - self.label_files = [path.replace('images', 'labels').replace('.png', '.txt').replace('.jpg', '.txt') for path in - self.img_files] + self.label_files = [path.replace('images', 'labels').replace('.png', '.txt').replace('.jpg', '.txt') + for path in self.img_files] self.nF = len(self.img_files) # number of image files self.nB = math.ceil(self.nF / batch_size) # number of batches @@ -73,7 +72,7 @@ class load_images_and_labels(): # for training self.multi_scale = multi_scale self.augment = augment - assert self.nB > 0, 'No images found in path %s' % path + assert self.nB > 0, 'No images found in %s' % path def __iter__(self): self.count = -1 @@ -128,7 +127,7 @@ class load_images_and_labels(): # for training cv2.cvtColor(img_hsv, cv2.COLOR_HSV2BGR, dst=img) h, w, _ = img.shape - img, ratio, padw, padh = letterbox(img, height=height, color=(127.5, 127.5, 127.5)) + img, ratio, padw, padh = letterbox(img, height=height) # Load labels if os.path.isfile(label_path): @@ -189,7 +188,7 @@ class load_images_and_labels(): # for training return self.nB # number of batches -def letterbox(img, height=416, color=(0, 0, 0)): # resize a rectangular image to a padded square +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))