如何提取或获取 Detectron 包围的图像

Question

我正在使用我自己创建的训练数据集在检测的帮助下在图像上创建边界框，而我现在陷入了提取有界图像的部分。 我只想要边界框内零件的图像。 要预测的输入图像。

带有边界框轮廓的预测图像。

请帮助我完成此查询。结果图像应该是这样的。

Answer 1

Tensorflow方法中的检测功能

 # Detection Function
 detections = detect_fn(input_tensor)

 bscores = detections['detection_scores'][0].numpy()
 bclasses = detections['detection_classes'][0].numpy().astype(np.int32)
 bboxes = detections['detection_boxes'][0].numpy()

 det_boxes, class_labels = ExtractBBoxes(bboxes, bclasses, bscores, im_width, im_height, image_name=image_file)

提取和裁剪边界框

def ExtractBBoxes(bboxes, bclasses, bscores, im_width, im_height, image_name):
 bbox = []
 class_labels = []
 for idx in range(len(bboxes)):
    if bscores[idx] >= Threshold:
      #Region of Interest
      y_min = int(bboxes[idx][0] * im_height)
      x_min = int(bboxes[idx][1] * im_width)
      y_max = int(bboxes[idx][2] * im_height)
      x_max = int(bboxes[idx][3] * im_width)
      class_label = category_index[int(bclasses[idx])]['name']
      class_labels.append(class_label)
      bbox.append([x_min, y_min, x_max, y_max, class_label, float(bscores[idx])])

      #Crop Image
      cropped_image = tf.image.crop_to_bounding_box(image, y_min, x_min, y_max - y_min, x_max - x_min).numpy().astype(np.int32)
      output_image = tf.image.encode_jpeg(cropped_image) #For Jpeg
      score = bscores[idx] * 100
      # Create a constant as filename
      file_name = tf.constant(youfilename)
      file = tf.io.write_file(file_name, output_image)