Update main.py

main.py

@@ -1,17 +1,14 @@
-from fastapi import FastAPI, File, UploadFile
+from fastapi import FastAPI, File, UploadFile, Form
 from fastapi.middleware.cors import CORSMiddleware
-from typing import List
+from typing import List, Optional
 from sahi import AutoDetectionModel
 from sahi.predict import get_sliced_prediction
-from PIL import Image, ExifTags
 import uvicorn
 import shutil
 import os
-import io
 
 app = FastAPI()
 
-# SECURITY: Allow access
 app.add_middleware(
     CORSMiddleware,
     allow_origins=["*"], 
@@ -20,14 +17,12 @@ app.add_middleware(
     allow_headers=["*"],
 )
 
-# ==========================================
-# 🧠 LOAD SAHI MODEL
-# ==========================================
+# 🧠 LOAD MODEL
 print("⏳ Loading SAHI + YOLO Model...")
 try:
     detection_model = AutoDetectionModel.from_pretrained(
         model_type='yolov8',
-        model_path='best.pt',    # Your trained model
+        model_path='best.pt',
         confidence_threshold=0.25,
         device='cpu'             
     )
@@ -35,53 +30,7 @@ try:
 except Exception as e:
     print(f"❌ Error loading model: {e}")
 
-# ==========================================
-# 📍 GPS HELPER FUNCTIONS (NEW)
-# ==========================================
-def get_decimal_from_dms(dms, ref):
-    degrees = dms[0]
-    minutes = dms[1]
-    seconds = dms[2]
-    decimal = degrees + (minutes / 60.0) + (seconds / 3600.0)
-    if ref in ['S', 'W']:
-        decimal = -decimal
-    return decimal
-
-def get_image_coordinates(image):
-    try:
-        exif_data = image._getexif()
-        if not exif_data:
-            return None, None
-
-        gps_info = {}
-        for tag, value in exif_data.items():
-            decoded = ExifTags.TAGS.get(tag, tag)
-            if decoded == "GPSInfo":
-                gps_info = value
-                break
-        
-        if not gps_info:
-            return None, None
-
-        # Extract Lat/Lon
-        lat_dms = gps_info.get(2) # GPSLatitude
-        lat_ref = gps_info.get(1) # GPSLatitudeRef
-        lon_dms = gps_info.get(4) # GPSLongitude
-        lon_ref = gps_info.get(3) # GPSLongitudeRef
-
-        if lat_dms and lat_ref and lon_dms and lon_ref:
-            lat = get_decimal_from_dms(lat_dms, lat_ref)
-            lon = get_decimal_from_dms(lon_dms, lon_ref)
-            return lat, lon
-            
-    except Exception as e:
-        print(f"⚠️ GPS Extract Error: {e}")
-        return None, None
-    
-    return None, None
-
-
-# Helper function for recommendations
+# Helper for recommendations
 def get_recommendation(disease_name):
     recommendations = {
         "Blast": "Use Tricyclazole 75 WP. Avoid excess nitrogen.",
@@ -95,28 +44,25 @@ def get_recommendation(disease_name):
 
 @app.get("/")
 def home():
-    return {"message": "Goyam AI (SAHI Enabled) is Running! 🚀"}
+    return {"message": "Goyam AI is Running! 🚀"}
 
 # ---------------------------------------------------------
-# 1. SINGLE IMAGE PREDICTION (Updated for GPS)
+# 1. PREDICT ENDPOINT (Now accepts explicit GPS)
 # ---------------------------------------------------------
 @app.post("/predict")
-async def predict(file: UploadFile = File(...)):
+async def predict(
+    file: UploadFile = File(...),
+    latitude: Optional[str] = Form(None),  # 👈 New text field
+    longitude: Optional[str] = Form(None)  # 👈 New text field
+):
     print(f"📥 Receiving image: {file.filename}")
+    print(f"📍 Received GPS: {latitude}, {longitude}")
     
-    # Read file into memory to extract GPS + Save temp
-    image_bytes = await file.read()
-    image_pil = Image.open(io.BytesIO(image_bytes))
-    
-    # 📍 Extract GPS
-    lat, lon = get_image_coordinates(image_pil)
-    print(f"📍 Found Location: {lat}, {lon}")
-
-    # Save temp file for SAHI
     temp_filename = f"temp_{file.filename}"
     try:
+        # Save temp file
         with open(temp_filename, "wb") as buffer:
-            buffer.write(image_bytes)
+            shutil.copyfileobj(file.file, buffer)
 
         # Run SAHI
         result = get_sliced_prediction(
@@ -130,10 +76,11 @@ async def predict(file: UploadFile = File(...)):
         
         predictions = result.object_prediction_list
         
+        # Prepare Response
         response_data = {
             "filename": file.filename,
-            "latitude": lat,  # 👈 Sending GPS back
-            "longitude": lon  # 👈 Sending GPS back
+            "latitude": float(latitude) if latitude else None,
+            "longitude": float(longitude) if longitude else None
         }
 
         if len(predictions) > 0: