How to count objects in Tensorflow Object Detection API

Question

I am executing https://github.com/tensorflow/tensorflow this example of detecting objects in image.

I want to get count of detected objects following is the code that gives me detected object drawn in an image. But I am not able to get count of detected objects.

with detection_graph.as_default():
with tf.Session(graph=detection_graph) as sess:
    for image_path in TEST_IMAGE_PATHS:
      image = Image.open(image_path)
      # the array based representation of the image will be used later in order to prepare the
      # result image with boxes and labels on it.
      image_np = load_image_into_numpy_array(image)
      # Expand dimensions since the model expects images to have shape: [1, None, None, 3]
      image_np_expanded = np.expand_dims(image_np, axis=0)
      image_tensor = detection_graph.get_tensor_by_name('image_tensor:0')
      # Each box represents a part of the image where a particular object was detected.
      boxes = detection_graph.get_tensor_by_name('detection_boxes:0')
      # Each score represent how level of confidence for each of the objects.
      # Score is shown on the result image, together with the class label.
      scores = detection_graph.get_tensor_by_name('detection_scores:0')
      classes = detection_graph.get_tensor_by_name('detection_classes:0')
      num_detections = detection_graph.get_tensor_by_name('num_detections:0')
      # Actual detection.
      (boxes, scores, classes, num_detections) = sess.run(
          [boxes, scores, classes, num_detections],
          feed_dict={image_tensor: image_np_expanded})
      # Visualization of the results of a detection.
      vis_util.visualize_boxes_and_labels_on_image_array(
          image_np,
          np.squeeze(boxes),
          np.squeeze(classes).astype(np.int32),
          np.squeeze(scores),
          category_index,
          use_normalized_coordinates=True,
          line_thickness=1)
      plt.figure(figsize=IMAGE_SIZE)
      plt.imshow(image_np)

This is the block of code that gives actual object detection shown in below image:

How can I get the object count?

Answer 1

You should check scores and count objects as manual. Code is here:

#code to test image start

    (boxes, scores, classes, num) = sess.run(
        [detection_boxes, detection_scores, detection_classes, num_detections],
        feed_dict={image_tensor: image_np_expanded})

#code to test image finish

#add this part to count objects

    final_score = np.squeeze(scores)    
        count = 0
        for i in range(100):
            if scores is None or final_score[i] > 0.5:
                    count = count + 1

#count is the number of objects detected

Answer 2

You can use the TensorFlow Object Counting API that is an open source framework built on top of TensorFlow that makes it easy to develop object counting systems to count any objects! Moreover, it provides sample projects so you can adopt them to develop your own specific case studies!

• Sample Project#1 is "Pedestrian Counting":

• Sample Project#2 is "Vehicle Counting":

• Sample Project#3 is "Object Counting in Real-Time":

See the TensorFlow Object Counting API for more info and please give a star that repo for showing your support to open source community if you find it useful!