コード例 #1
0
ファイル: fasterrcnn_loader.py プロジェクト: yobcmst/torchcv
    def __list_dirs(self, root_dir, dataset):
        img_list = list()
        json_list = list()
        image_dir = os.path.join(root_dir, dataset, 'image')
        json_dir = os.path.join(root_dir, dataset, 'json')

        for file_name in os.listdir(json_dir):
            image_name = '.'.join(file_name.split('.')[:-1])
            img_path = ImageHelper.imgpath(image_dir, image_name)
            json_path = os.path.join(json_dir, file_name)
            if not os.path.exists(json_path) or img_path is None:
                Log.warn('Json Path: {} not exists.'.format(json_path))
                continue

            json_list.append(json_path)
            img_list.append(img_path)

        if dataset == 'train' and self.configer.get('data', 'include_val'):
            image_dir = os.path.join(root_dir, 'val/image')
            json_dir = os.path.join(root_dir, 'val/json')
            for file_name in os.listdir(json_dir):
                image_name = '.'.join(file_name.split('.')[:-1])
                img_path = ImageHelper.imgpath(image_dir, image_name)
                json_path = os.path.join(json_dir, file_name)
                if not os.path.exists(json_path) or img_path is None:
                    Log.warn('Json Path: {} not exists.'.format(json_path))
                    continue

                json_list.append(json_path)
                img_list.append(img_path)

        return img_list, json_list
コード例 #2
0
    def __list_dirs(self, root_dir, dataset):
        imgA_list = list()
        imgB_list = list()

        imageA_dir = os.path.join(root_dir, dataset, 'imageA')
        imageB_dir = os.path.join(root_dir, dataset, 'imageB')

        for file_name in os.listdir(imageA_dir):
            image_name = '.'.join(file_name.split('.')[:-1])
            imgA_path = ImageHelper.imgpath(imageA_dir, image_name)
            imgB_path = ImageHelper.imgpath(imageB_dir, image_name)
            if not os.path.exists(imgA_path) or not os.path.exists(imgB_path):
                Log.warn('Img Path: {} not exists.'.format(imgA_path))
                continue

            imgA_list.append(imgA_path)
            imgB_list.append(imgB_path)

        if dataset == 'train' and self.configer.get('data', 'include_val'):
            imageA_dir = os.path.join(root_dir, 'val/imageA')
            imageB_dir = os.path.join(root_dir, 'val/imageB')
            for file_name in os.listdir(imageA_dir):
                image_name = '.'.join(file_name.split('.')[:-1])
                imgA_path = ImageHelper.imgpath(imageA_dir, image_name)
                imgB_path = ImageHelper.imgpath(imageB_dir, image_name)
                if not os.path.exists(imgA_path) or not os.path.exists(
                        imgB_path):
                    Log.warn('Img Path: {} not exists.'.format(imgA_path))
                    continue

                imgA_list.append(imgA_path)
                imgB_list.append(imgB_path)

        return imgA_list, imgB_list