I am trying to use human pose estimation through keras implementation. I am using this source https://github.com/michalfaber/keras_Realtime_Multi-Person_Pose_Estimation. My problem is how can I generate the skeleton view of the following image, the one on the left part? However, I can generate the one on the right part.
** Source Photograph taken from Pexels
Below is the code I am using to achieve this.
# vgg normalization (subtracting mean) on input images
model = get_testing_model()
model.load_weights(keras_weights_file)
# load config
params, model_params = config_reader()
input_image = cv2.imread(image_path) # B,G,R order
body_parts, all_peaks, subset, candidate = extract_parts(input_image, params, model, model_params)
canvas = draw(input_image, all_peaks, subset, candidate)
toc = time.time()
print('processing time is %.5f' % (toc - tic))
cv2.imwrite(output, canvas)
cv2.destroyAllWindows()
You need to draw over black image not input image for your requirement. Here below in the updated code.
# vgg normalization (subtracting mean) on input images
model = get_testing_model()
model.load_weights(keras_weights_file)
# load config
params, model_params = config_reader()
input_image = cv2.imread(image_path) # B,G,R order
body_parts, all_peaks, subset, candidate = extract_parts(input_image, params, model, model_params)
black_img = np.zeros_like(input_image, np.uint8)
canvas = draw(black_img, all_peaks, subset, candidate)
toc = time.time()
print('processing time is %.5f' % (toc - tic))
cv2.imwrite(output, canvas)
cv2.destroyAllWindows()