__init__.py 文件源码

def __getitem__(self, index):
        datafiles = self.files[index]

        image = cv2.imread(datafiles["img"], cv2.IMREAD_COLOR)
        label = cv2.imread(datafiles["label"], cv2.IMREAD_GRAYSCALE)
        size = image.shape
        name = datafiles["name"]

        if self.scale:
            image, label = self.generate_scale_label(image, label)

        image = np.asarray(image, np.float32)
        image -= self.mean
        img_h, img_w = label.shape
        pad_h = max(self.crop_h - img_h, 0)
        pad_w = max(self.crop_w - img_w, 0)
        if pad_h > 0 or pad_w > 0:
            img_pad = cv2.copyMakeBorder(image, 0, pad_h, 0, 
                pad_w, cv2.BORDER_CONSTANT, 
                value=(0.0, 0.0, 0.0))
            label_pad = cv2.copyMakeBorder(label, 0, pad_h, 0, 
                pad_w, cv2.BORDER_CONSTANT,
                value=(self.ignore_label,))
        else:
            img_pad, label_pad = image, label
        img_h, img_w = label_pad.shape

        h_off = random.randint(0, img_h - self.crop_h)
        w_off = random.randint(0, img_w - self.crop_w)

        # roi = cv2.Rect(w_off, h_off, self.crop_w, self.crop_h);
        image = np.asarray(img_pad[h_off : h_off+self.crop_h, w_off : w_off+self.crop_w], np.float32)
        label = np.asarray(label_pad[h_off : h_off+self.crop_h, w_off : w_off+self.crop_w], np.float32)
        #image = image[:, :, ::-1]  # change to BGR
        image = image.transpose((2, 0, 1))
        if self.is_mirror:
            flip = np.random.choice(2) * 2 - 1
            image = image[:, :, ::flip]
            label = label[:, ::flip]

        return image.copy(), label.copy(), np.array(size), name