error handle

HDML-FaceDetection.log

@@ -1 +0,0 @@
-Time:05:29:53 PM, Execution Done and Total Successfull Execution : 1, Payload:url='https://bl-bucket.sgp1.digitaloceanspaces.com/pulse/faceDetection/lvglbz46yd9et1qknf/faceDetection-original', Result:{}

README.MD

@@ -1,5 +0,0 @@
-### Himel_Face_Detection
-
-# Himel app 
-------------
-ngrok config add-authtoken 2Qm8hS1zPhVXiLjEdlI4738tLzF_2QJwGJMK5oTbQD33QSVXS && sudo apt update && sudo apt upgrade && ngrok http --domain=hawkeyes.ngrok.app 8000

README.md

@@ -0,0 +1,14 @@
+### rakib72642/HDML_Face_Detection_Model
+
+# HuggingFace: https://huggingface.co/rakib72642/HDML_Face_Detection_Model
+
+# Setup Global API
+
+sudo apt install iproute2 -y && sudo apt install wget -y && sudo apt install unzip -y && sudo apt install unzip -y && apt install nvtop -y && sudo apt-get install git-all -y && sudo apt-get install git-lfs -y && sud apt-get update && sudo apt-get install libgl1 -y && sudo apt install curl -y &&  curl -s https://ngrok-agent.s3.amazonaws.com/ngrok.asc | sudo tee /etc/apt/trusted.gpg.d/ngrok.asc >/dev/null && echo "deb https://ngrok-agent.s3.amazonaws.com buster main" | sudo tee /etc/apt/sources.list.d/ngrok.list && sudo apt update && sudo apt install ngrok -y && sudo apt update && sudo apt upgrade -y && ngrok config add-authtoken 2Qm8hS1zPhVXiLjEdlI4738tLzF_2QJwGJMK5oTbQD33QSVXS && ngrok http --domain=hawkeyes.ngrok.app 8585
+
+# Setup Local API
+git clone https://huggingface.co/rakib72642/HDML_Face_Detection_Model && cd HDML_Face_Detection_Model && pip install -r requirements.txt && sudo apt update && sudo apt upgrade -y  && python face_main.py
+
+cd HDML_Face_Detection_Model && python face_main.py
+
+# hypercorn face_main:app --bind 127.0.0.1:8585 --workers 4

face_api.py

@@ -1,4 +1,4 @@
-from fastapi import FastAPI
+from fastapi import FastAPI, HTTPException
 from pydantic import BaseModel
 import asyncio
 from typing import List, Union
@@ -37,21 +37,25 @@ async def process_item(item: Item):
         result = await mainDet(item.url)
         result = json.loads(result)
         return result
+    except Exception as e:
+        raise ValueError(f"process_item ERROR : {str(e)}")
     finally:
         torch.cuda.empty_cache()
-        pass
 
 async def process_items(items: Union[Item, List[Item]]):
-    print(type(items))
-    if type(items)==list:
-        coroutines = [process_item(item) for item in items]
-        results = await asyncio.gather(*coroutines)
-        print("multi : ",results)
-    else:
-        results = await process_item(items)
-        print("single : ", results)
-    return results
-
+    try:
+        if type(items)==list:
+            coroutines = [process_item(item) for item in items]
+            results = await asyncio.gather(*coroutines)
+            print("multi : ",results)
+        else:
+            results = await process_item(items)
+            print("single : ", results)
+        return results
+    except Exception as e:
+        raise ValueError(f"process_items ERROR : {str(e)}")
+    finally:
+        torch.cuda.empty_cache()
 
 
 @app.get("/status")
@@ -72,17 +76,18 @@ async def create_items(items: Union[Item, List[Item]]):
         total_error += 1
         logger.info(f"Time:{get_bd_time()}, Execution Failed and Total Failed Execution : {total_error}, Payload:{items}, Error:{str(e)}")
         logger.error(str(e))
-        return {"AI": f"Error: {str(e)}"}
+        raise ValueError(f"process_item ERROR : {str(e)}")
     finally:
         global total_done
         total_done +=1
         logger.info(f"Time:{get_bd_time()}, Execution Done and Total Successfull Execution : {total_done}, Payload:{items}, Result:{results}")
         torch.cuda.empty_cache()
-        pass
 
 if __name__ == "__main__":
     try:
         del faceModel
         uvicorn.run(app, host="127.0.0.1", port=8585)
+    except Exception as e:
+        raise ValueError(f"face_api ERROR : {str(e)}")
     finally:
         torch.cuda.empty_cache()

face_main.py

@@ -2,6 +2,7 @@ import json
 import pandas as pd
 import asyncio
 import base64
+import torch
 from PIL import Image, ImageDraw
 from aiohttp import ClientSession
 from io import BytesIO
@@ -16,7 +17,9 @@ async def getImage(img_url):
                 img_data = await response.read()
                 return BytesIO(img_data)
         except Exception as e:
-            print({"Error in getImage":str(e)})
+            raise ValueError(f"getImage ERROR : {str(e)}")
+        finally:
+            torch.cuda.empty_cache()
 
 
 async def detection(model,img_content):
@@ -38,7 +41,10 @@ async def detection(model,img_content):
                 detection.update(res)
         return detection
     except Exception as e:
-        print({"Error in detection":str(e)})
+        raise ValueError(f"detection ERROR : {str(e)}")
+    finally:
+        torch.cuda.empty_cache()
+
 
 
 
@@ -51,11 +57,9 @@ async def format_result(ai_result,convert_data):
                 result.update({i:member_details[i]})
         return result
     except Exception as e:
-        print({"Error in format_result":str(e)})
-
-
-
-
+        raise ValueError(f"format_result ERROR : {str(e)}")
+    finally:
+        torch.cuda.empty_cache()
 
 
 async def mainDet(url):
@@ -64,7 +68,8 @@ async def mainDet(url):
         detect_data = await asyncio.create_task(detection(faceModel, image))
         result = await asyncio.create_task(format_result(detect_data,member_details))
         return json.dumps(result)
-
     except Exception as e:
-        print({"Error in mainDet":str(e)})
+        raise ValueError(f"mainDet ERROR : {str(e)}")
+    finally:
+        torch.cuda.empty_cache()
 

requirements.txt

@@ -0,0 +1,9 @@
+fastapi
+pydantic
+uvicorn
+hypercorn
+pytz
+httpx
+requests
+aiofiles
+ultralytics