def my_read_frame(frame_dir, transforms, scale_size):
"""
read a single frame & preprocess
"""
frame = cv2.imread(frame_dir, cv2.IMREAD_COLOR)
ori_h,ori_w,_ = frame.shape
# scale, makes height & width multiples of 64
if(len(scale_size) == 1):
if(ori_h > ori_w):
tw = scale_size[0]
th = (tw * ori_h) / ori_w
th = int((th // 64) * 64)
else:
th = scale_size[0]
tw = (th * ori_w) / ori_h
tw = int((tw // 64) * 64)
else:
tw = scale_size[1]
th = scale_size[0]
frame = cv2.resize(frame, (640,640))
img = copy.deepcopy(frame)
img = np.array(img, dtype=np.float32)
img = img / 255
meanval = [0.485, 0.456, 0.406]
std = [0.229, 0.224, 0.225]
img = np.subtract(img, np.array(meanval, dtype=np.float32))
img = img / std
img = img.transpose((2, 0, 1))
img = torch.from_numpy(img).float()
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2LAB)
pair = [frame, frame]
transformed = list(transforms(*pair))
return transformed[0].cuda().unsqueeze(0), ori_h, ori_w, img.cuda().unsqueeze(0)
def read_frame(frame_dir, transforms, scale_size):
"""
read a single frame & preprocess
"""
frame = cv2.imread(frame_dir)
ori_h,ori_w,_ = frame.shape
# scale, makes height & width multiples of 64
if(len(scale_size) == 1):
if(ori_h > ori_w):
tw = scale_size[0]
th = (tw * ori_h) / ori_w
th = int((th // 64) * 64)
else:
th = scale_size[0]
tw = (th * ori_w) / ori_h
tw = int((tw // 64) * 64)
else:
tw = scale_size[1]
th = scale_size[0]
frame = cv2.resize(frame, (tw,th))
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2LAB)
pair = [frame, frame]
transformed = list(transforms(*pair))
return transformed[0].cuda().unsqueeze(0), ori_h, ori_w
def read_frame(frame_dir, transforms):
frame = cv2.imread(frame_dir)
ori_h, ori_w, _ = frame.shape
if (ori_h > ori_w):
tw = ori_w
th = (tw * ori_h) / ori_w
th = int((th // 64) * 64)
else:
th = ori_h
tw = (th * ori_w) / ori_h
tw = int((tw // 64) * 64)
#h = (ori_h // 64) * 64
#w = (ori_w // 64) * 64
frame = cv2.resize(frame, (tw, th))
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2LAB)
pair = [frame, frame]
transformed = list(transforms(*pair))
return transformed[0].cuda().unsqueeze(0), ori_h, ori_w