salto alto exercise

app.py

@@ -1,12 +1,21 @@
-from fastapi import FastAPI, UploadFile, File, Response,Header, BackgroundTasks,Body,HTTPException
+from fastapi import (FastAPI,
+                     UploadFile,
+                     File,
+                     Header,
+                     BackgroundTasks,
+                     Body,
+                     HTTPException)
+
 from fastapi.staticfiles import StaticFiles
 from vitpose import VitPose
 from dotenv import load_dotenv
 from tasks import process_video,process_salto_alto
 from fastapi.responses import JSONResponse
 from config import AI_API_TOKEN
-from typing import Any
 import logging
+
+
+
 logging.basicConfig(level=logging.INFO)
 logger = logging.getLogger(__name__)
 app = FastAPI()
@@ -34,7 +43,8 @@ async def upload(background_tasks: BackgroundTasks,
                  player_id: str = Body(...)):
     
     if token != AI_API_TOKEN:
-        return JSONResponse(content={"message": "Unauthorized", "status": 401})
+        return JSONResponse(content={"message": "Unauthorized", 
+                                     "status": 401})
     
     logger.info("reading contents")
     contents = await file.read()
@@ -47,10 +57,15 @@ async def upload(background_tasks: BackgroundTasks,
     logger.info(f"file saved {file.filename}")
     
     # Create a clone of the file with content already read
-    background_tasks.add_task(process_video, file.filename, vitpose, user_id,player_id)  
+    background_tasks.add_task(process_video, 
+                              file.filename,
+                              vitpose,
+                              user_id,
+                              player_id)  
 
     # Return the file as a response
-    return JSONResponse(content={"message": "Video uploaded successfully", "status": 200})
+    return JSONResponse(content={"message": "Video uploaded successfully", 
+                                 "status": 200})
     
 @app.post("/exercise/salto_alto")
 async def upload(background_tasks: BackgroundTasks,
@@ -83,9 +98,10 @@ async def upload(background_tasks: BackgroundTasks,
                               file.filename,
                               vitpose, 
                               player_data,
-                              repetitions,
-                              exercise_id)  
+                              exercise_id,
+                              repetitions)  
 
     # Return the file as a response
     print(f"returning response")
-    return JSONResponse(content={"message": "Video uploaded successfully", "status": 200})
+    return JSONResponse(content={"message": "Video uploaded successfully",
+                                 "status": 200})

tasks.py

@@ -9,6 +9,7 @@ import numpy as np
 
 import time
 import json
+from fastapi.responses import JSONResponse
 
 logging.basicConfig(level=logging.INFO)
 logger = logging.getLogger(__name__)
@@ -55,8 +56,8 @@ def process_video(file_name: str,vitpose: VitPose,user_id: str,player_id: str):
 def process_salto_alto(file_name: str,
                        vitpose: VitPose,
                        player_data: dict,
-                       repetitions: int,
-                       exercise_id: str) -> dict:
+                       exercise_id: str,
+                       repetitions) -> dict:
     """
     Process a high jump exercise video using VitPose for pose estimation.
     
@@ -80,14 +81,14 @@ def process_salto_alto(file_name: str,
     output_video = file_name.replace('.mp4', '_analyzed.mp4')    
     # Process the video and get the jump metrics
     # print(f"reference_height: {reference_height}")
-    # results_dict = analyze_jump_video(
-    #     model=model,
-    #     input_video=file_name,
-    #     output_video=output_video,
-    #     player_height= float(reference_height) / 100, #cm to m
-    #     body_mass_kg= float(body_mass_kg),
-    #     repetitions=repetitions
-    # )
+    results_dict = analyze_jump_video(
+        model=model,
+        input_video=file_name,
+        output_video=output_video,
+        player_height= float(reference_height) / 100, #cm to m
+        body_mass_kg= float(body_mass_kg),
+        repetitions=repetitions
+    )
     
     results_dict = {'video_analysis': {'output_video': 'user_id_2_player_id_2_exercise_salto_alto_VIDEO-2025-05-19-18-55-47_analyzed.mp4'}, 'repetition_data': [{'repetition': 1, 'distancia_elevada': 0.47999998927116394, 'salto_alto': 2.180000066757202, 'potencia_sayer': 3768.719970703125}, {'repetition': 2, 'distancia_elevada': 0.49000000953674316, 'salto_alto': 2.190000057220459, 'potencia_sayer': 3827.929931640625}, {'repetition': 3, 'distancia_elevada': 0.5099999904632568, 'salto_alto': 2.2100000381469727, 'potencia_sayer': 3915.5}]}
     
@@ -106,7 +107,7 @@ def process_salto_alto(file_name: str,
 def send_results_api(results_dict: dict,
                      player_id: str,
                      exercise_id: str,
-                     video_path: str):
+                     video_path: str) -> JSONResponse:
     """
     Updated function to send results to the new webhook endpoint
     """
@@ -164,6 +165,12 @@ def analyze_jump_video(model: VitPose,
     Returns:
         Dictionary containing jump metrics and video analysis data
     """
+    
+    
+    #TODO: REFACTOR THIS FUNCTION
+    
+    
+    
     # Configuration parameters
     JUMP_THRESHOLD_PERCENT = 0.05  # Porcentaje de cambio en la altura del tobillo para detectar el inicio del salto
     SMOOTHING_WINDOW = 5  # Ventana para suavizar la altura de los tobillos
@@ -539,6 +546,11 @@ def draw_metrics_overlay(frame, max_jump_height, salto_alto, velocity_vertical,
     Returns:
         Frame with metrics overlay
     """
+    
+     
+    #TODO: REFACTOR THIS FUNCTION
+    
+    
     overlay = frame.copy()
     alpha = 0.7
     font = cv2.FONT_HERSHEY_SIMPLEX