changes model

main.py

@@ -1,16 +1,16 @@
 from fastapi import FastAPI,UploadFile,File,HTTPException
 from transformers import pipeline
-from facenet_pytorch import MTCNN
+# from facenet_pytorch import MTCNN
 from PIL import Image
 import io
 
 app=FastAPI(title="Deepfake")
 
-print("Face Detector Loading...")
-mtcnn=MTCNN(keep_all=False,device='cpu')
+# print("Face Detector Loading...")
+# mtcnn=MTCNN(keep_all=False,device='cpu')
 
 print("Deepfake AI Loading...")
-pipe=pipeline("image-classification",model="dima806/deepfake_vs_real_image_detection")
+pipe=pipeline("image-classification",model="haywoodsloan/ai-image-detector-dev-deploy")
 print("All Systems Loaded!")
 
 @app.post("/api/v1/predict/image")
@@ -22,13 +22,13 @@ async def predict_image(file:UploadFile=File(...)):
         image_bytes=await file.read()
         image=Image.open(io.BytesIO(image_bytes)).convert("RGB")
         # check for human faces
-        boxes, _ =mtcnn.detect(image)
+        # boxes, _ =mtcnn.detect(image)
         
-        if boxes is None:
-            return {
-                "status":"failed",
-                "message":"No human face detected in the image. Please upload a clear human portrait."
-            }
+        # if boxes is None:
+        #     return {
+        #         "status":"failed",
+        #         "message":"No human face detected in the image. Please upload a clear human portrait."
+        #     }
 
         results=pipe(image)
         formatted_results={res['label'].lower(): round(res['score'] * 100, 2) for res in results}
@@ -36,7 +36,7 @@ async def predict_image(file:UploadFile=File(...)):
 
         return {
             "status":"success 200",
-            "faces_detected":len(boxes),
+            # "faces_detected":len(boxes),
             "verdict":verdict,
             "confidence":formatted_results[verdict]
         }