Update app.py

app.py

@@ -5,7 +5,6 @@ import supervision as sv
 from roboflow import Roboflow
 import tempfile
 import os
-from sahi import AutoDetectionModel
 from sahi.predict import predict
 from dotenv import load_dotenv
 
@@ -21,9 +20,6 @@ rf = Roboflow(api_key=api_key)
 project = rf.workspace(workspace).project(project_name)
 model = project.version(model_version).model
 
-# Initialize SAHI model for inference
-detection_model = AutoDetectionModel.from_pretrained(model)
-
 def detect_objects(image):
     # Save the uploaded image to a temporary file
     with tempfile.NamedTemporaryFile(delete=False, suffix=".jpg") as temp_file:
@@ -34,15 +30,15 @@ def detect_objects(image):
     original_image = cv2.imread(temp_file_path)
 
     try:
-        # Perform inference using SAHI Slicer
+        # Use SAHI to slice the image (optional for large images)
         predictions = predict(
-            detection_model=detection_model,
+            detection_model=model,  # Use Roboflow model for prediction
             image=original_image,
-            slice_height=800,  # Height of the slice
-            slice_width=800,   # Width of the slice
+            slice_height=800,  # Height of each slice
+            slice_width=800,   # Width of each slice
             overlap_height_ratio=0.2,
             overlap_width_ratio=0.2,
-            return_slice_result=False,
+            return_slice_result=False,  # We don't need slice results, just detections
         )
 
         # Initialize Supervision annotations