face_dataset.py 文件源码

def get_example(self, i):
        # type: (any) -> typing.Tuple[str, Image]
        path, image = super().get_example(i)
        image_array = numpy.asarray(image)
        image_height, image_width = image_array.shape[:2]
        if len(image_array.shape) == 2:  # gray image
            gray = image_array
        else:
            gray = cv2.cvtColor(image_array, cv2.COLOR_RGB2GRAY)
        facerects = self.classifier.detectMultiScale(
            gray,
            scaleFactor=1.1,
            minNeighbors=5,
            minSize=(64, 64))
        if len(facerects) == 0:
            return path, None  # more sophisticated way to handle errors?
        x, y, width, _ = facerects[0]
        margin = int(width * self.margin_ratio)
        if min(
                y, image_height - y - width,
                x, image_width - x - width,
        ) < margin:  # cannot crop
            return path, None

        cropped = image_array[y - margin:y + width + margin, x - margin:x + width + margin]
        if self.output_resize is None:
            return path, Image.fromarray(cropped)
        else:
            return path, Image.fromarray(cropped).resize(self.output_resize)