How to count objects in Tensorflow Object Detection API

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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?

TensorFlow Object Counting API, In other words, by only counting how many elements are in the box, you could know how many objects are in the image. You can find an example here: qdraw/​  TensorFlow Object Detection Supercharge your computer vision models with the TensorFlow Object Detection API. Artificial intelligence Can artificial intelligence identify pictures better than humans? From the developers IBM Visual Insights speeds transfer learning with greater accuracy -- a real world example.

Solve it simply print length of boxes.shape

print(len(boxes.shape))

How can tensorflow object detection API be used for object counting , The TensorFlow Object Counting API is an API for the TensorFlow. It is an open-​source framework built on top of TensorFlow and Keras that  TensorFlow’s object detection API is an open-source framework built on top of TensorFlow that makes it easy to construct, train, and deploy object detection models. People Counting. Object

It's important to note that the number of boxes is always 100.

If you look at the code that actually draws the boxes, i.e., the vis_util.visualize_boxes_and_labels_on_image_array function, you'll see that they're defining a threshold -- min_score_thresh=.5 -- to limit the boxes drawn to only those detections in which the score is > 0.5. You can think of this as only drawing boxes where the probability of accurate detection is >50%. You can adjust this threshold up or down to increase the number of boxes drawn. If you decrease it too low, however, you will get a lot of inaccurate boxes.

Tensorflow Count Objects in Image, Detect multiple objects within an image, with bounding boxes. the TensorFlow Lite APIs, you can download our starter object detection model  To access the individual detected objects for each image you have to follow the following chain of scripts: eval.py-> evaluator.py->object_detection_evaluation.py-> per_image_evaluation.py. In the last script you can count the detected objects and bounding boxes per image. You just have to save the numbers and sum them up over your entire dataset.

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

Object detection, This is where product recognition and product count in a shelf image came into objects to detect using a technique called TRANSFER LEARNING. Training Custom Object Detector - TensorFlow Object Detection API  Here are some cool capabilities of TensorFlow Object Counting API: Detect just the targeted objects. Detect all the objects. Count just the targeted objects. Count all the objects. Predict color of the targeted objects. Predict color of all the objects. Predict speed of the targeted objects.

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

this part will print count but will print it in continuous manner can it be used to print only once like final count = some value instead of printing it repeatedly

Tensorflow Series - #3 - Object Counting with Tensorflow, IBM Visual Insights Object Detection to detect and label objects within an image. a REST endpoint to let your app detect, locate, and count items in an image IBM Visual Insights presents REST APIs for inference operations. your computer vision models with the TensorFlow Object Detection API. The Tensorflow Object Detection API is an open source framework that allows you to use pretrained object detection models or create and train new models by making use of transfer learning. This is extremely useful because building an object detection model from scratch can be difficult and can take lots of computing power.

TensorFlow Object Counting API, The code of the Object Counting API, implemented with the YOLO algorithm and with the SORT algorithm object-counting object-counting-api object-counter yolo yolov2 object-detection opencv computer-vision vehicle-tracking vehicle-detection pedestrian-tracking pedestrian-detection yolo-object-counting-api tensorflow traffic-analysis

PRODUCT DETECTION AND COUNTING IN SUPER MARKET , we can add more preciseness and detect more objects by adding data and do more training :) Please click like and subscribe and leave comments and tell us what you think about this video or what

Locate and count items with object detection – IBM Developer, Assuming you have already used the API, you might have seen that when you execute TensorFlow’s sess.run() with the image tensor, the function returns several variables, including one that has all the detection boxes (tensor name detection_boxes:0 ). The important detail here is that that variable,

Comments
  • this gives me information of those classes. I need a count which I got from printing length of boxes.shape. Any ways thank you.
  • Here is an Object Counting API for TensorFlow: github.com/ahmetozlu/tensorflow_object_counting_api , you can use it to count objects and more for developing object detection and counting based projects..
  • if scores is None , does it mean it contain an object ?