Update app.py

app.py

@@ -134,8 +134,8 @@ def postprocessor(prediction, orig_img):
     distance = distanceCalculate(points[0], points[1])
     midpoints = midpoint(points[0], points[1])
     result_image = cv2.line(result_image, points[0], points[1], (0,0,255), 1)
-    result_image = cv2.putText(result_image,str(distance), (midpoints[0],midpoints[0]+10), cv2.FONT_HERSHEY_SIMPLEX, 0.40, (0,0,255), 1, cv2.LINE_AA)
-    return result_image 
+    # result_image = cv2.putText(result_image,str(distance), (midpoints[0],midpoints[0]+10), cv2.FONT_HERSHEY_SIMPLEX, 0.40, (0,0,255), 1, cv2.LINE_AA)
+    return result_image, distance 
 
 def distanceCalculate(p1, p2):
     """p1 and p2 in format (x1,y1) and (x2,y2) tuples"""
@@ -171,14 +171,15 @@ def predict(img):
     preprocessed_img, orig_img = preprocessor(raw_img)
     # infer
     prediction = infer(preprocessed_img)
-    keypoints_map = postprocessor(prediction, orig_img)
+    keypoints_map, distance_keypoints = postprocessor(prediction, orig_img)
     # cv2.imwrite("keypoints_map.png", keypoints_map[:,:,::-1])
-    return keypoints_map
+    display_text  = "The distance between two key points A and B is {distance_keypoints} pixel units"
+    return keypoints_map, display_text
     
 
 gr.Interface(fn=predict,
              inputs=[gr.Image(shape=(224,224),type="filepath")],
-             outputs=[gr.Image(shape=(224,224))],
+             outputs=[gr.Image(shape=(224,224)), "text"],
              css="footer {visibility: hidden} body}, .gradio-container {background-color: white}",
              title="Automi Demo",
              examples=["001.png","002.png","003.png","004.png","005.png"]).launch(share=False)