plt.imshow not working

[Deepthi-Jain]

Hi All,

Thanks for the tutorial provided.

I have problem running the examples/custom trained models. Everything runs properly but the output image window doesn't appear.

Thanks in advance.

Regards,
Deepthi

[sglvladi]

@Deepthi-Jain adding a plt.show() at the end of the script should do the trick

[sglvladi]

Closing due to inactivity. Feel welcome to re-open if needed.

[Vlaxtocia]

Will this work in windows systems? I've got the code from one of your examples, but no output images show, it has the plt.show() at the end by default

for image_path in TEST_IMAGE_PATHS:

    print('Running inference for {}... '.format(image_path), end='')

    image_np = load_image_into_numpy_array(image_path)

    # Things to try:
    # Flip horizontally
    # image_np = np.fliplr(image_np).copy()

    # Convert image to grayscale
    # image_np = np.tile(
    #     np.mean(image_np, 2, keepdims=True), (1, 1, 3)).astype(np.uint8)

    # The input needs to be a tensor, convert it using `tf.convert_to_tensor`.
    input_tensor = tf.convert_to_tensor(image_np)
    # The model expects a batch of images, so add an axis with `tf.newaxis`.
    input_tensor = input_tensor[tf.newaxis, ...]

    # input_tensor = np.expand_dims(image_np, 0)
    detections = detect_fn(input_tensor)

    # All outputs are batches tensors.
    # Convert to numpy arrays, and take index [0] to remove the batch dimension.
    # We're only interested in the first num_detections.
    num_detections = int(detections.pop('num_detections'))
    detections = {key: value[0, :num_detections].numpy()
                   for key, value in detections.items()}
    detections['num_detections'] = num_detections

    # detection_classes should be ints.
    detections['detection_classes'] = detections['detection_classes'].astype(np.int64)

    image_np_with_detections = image_np.copy()

    viz_utils.visualize_boxes_and_labels_on_image_array(
          image_np_with_detections,
          detections['detection_boxes'],
          detections['detection_classes'],
          detections['detection_scores'],
          category_index,
          use_normalized_coordinates=True,
          max_boxes_to_draw=200,
          min_score_thresh=.30,
          agnostic_mode=False)

    plt.figure()
    plt.imshow(image_np_with_detections)
    print('Done')
plt.show()

[sglvladi]

@Vlaxtocia I primarily work on Windows, so it should work fine. Make sure this is not an issue relating to the default backend used by matplotlib (e.g. see here)