added pose related api documentation (#129)

* added poses example code to readme

* using urls in example to make it runnable

* added comment

README.md

@@ -39,29 +39,56 @@ when using this project as a library:
 ## Python API
 
 ```python
+from pathlib import Path
 import tensorflow as tf
 from tf_bodypix.api import download_model, load_model, BodyPixModelPaths
 
+# setup input and output paths
+output_path = Path('./data/example-output')
+output_path.mkdir(parents=True, exist_ok=True)
+input_url = (
+    'https://www.dropbox.com/s/7tsaqgdp149d8aj/serious-black-businesswoman-sitting-at-desk-in-office-5669603.jpg?dl=1'
+)
+local_input_path = tf.keras.utils.get_file(origin=input_url)
+
+# load model (once)
 bodypix_model = load_model(download_model(
     BodyPixModelPaths.MOBILENET_FLOAT_50_STRIDE_16
 ))
 
-image = tf.keras.preprocessing.image.load_img(
-    '/path/to/input-image.jpg'
-)
+# get prediction result
+image = tf.keras.preprocessing.image.load_img(local_input_path)
 image_array = tf.keras.preprocessing.image.img_to_array(image)
 result = bodypix_model.predict_single(image_array)
+
+# simple mask
 mask = result.get_mask(threshold=0.75)
 tf.keras.preprocessing.image.save_img(
-    '/path/to/output-mask.jpg',
+    f'{output_path}/output-mask.jpg',
     mask
 )
 
+# colored mask (separate colour for each body part)
 colored_mask = result.get_colored_part_mask(mask)
 tf.keras.preprocessing.image.save_img(
-    '/path/to/output-colored-mask.jpg',
+    f'{output_path}/output-colored-mask.jpg',
     colored_mask
 )
+
+# poses
+from tf_bodypix.draw import draw_poses  # utility function using OpenCV
+
+poses = result.get_poses()
+image_with_poses = draw_poses(
+    image_array.copy(),  # create a copy to ensure we are not modifing the source image
+    poses,
+    keypoints_color=(255, 100, 100),
+    skeleton_color=(100, 100, 255)
+)
+tf.keras.preprocessing.image.save_img(
+    f'{output_path}/output-poses.jpg',
+    image_with_poses
+)
 ```
 
 ## CLI