CODEWITHSUNDEEP
image-segmentationimage-recognitionfaster-rcnndetectronlabelimg
Rahul Sawant
Rahul Sawant

Reputation: 23

How to extract or get the image bounded by Detectron

I am working on creating bounding boxes upon images with my own created training dataset with the help of Detection, while I'm now stuck at the part of extracting the bounded image. I just want the image of the part inside the bounding box. The input image to predicted.

The predicted image with the bounding box outlines.

Please help me with this query.The resultant image should be like this.

Upvotes: 2

Views: 468

Answers (1)

ZKS
ZKS

Reputation: 2836

Detection Function in Tensorflow

 # 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)

Method to extract and crop bounding box

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)

Upvotes: 1

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