Update app.py

app.py

@@ -1,37 +1,25 @@
-import gradio as gr
-import cv2
-import os, sys
-
-# ✅ Fix: Add services/ to path manually
-sys.path.append(os.path.join(os.path.dirname(__file__), "services"))
-
-from video_service import get_video_frame
-from detection_service import detect_objects
-from thermal_service import detect_thermal_anomalies
-from shadow_detection import detect_shadow_coverage
-from salesforce_dispatcher import send_to_salesforce
-
-frame_gen = get_video_frame("data/sample_pole_video.mp4")
-
-def monitor_feed():
-    try:
-        frame = next(frame_gen)
-        cv2.imwrite("temp.jpg", frame)
-
-        detections = detect_objects("temp.jpg")
-        thermal = detect_thermal_anomalies("temp.jpg")
-        shadow_flag = detect_shadow_coverage("temp.jpg")
-
-        alert_payload = {
-            "detections": detections,
-            "thermal": bool(thermal),
-            "shadow_issue": shadow_flag,
-        }
-
-        send_to_salesforce(alert_payload)
-        return frame
-    except StopIteration:
-        return None
-
-iface = gr.Interface(fn=monitor_feed, inputs=[], outputs="image", live=True, title="VIEP Smart Pole Video Fault Detector")
-iface.launch()
+# Import necessary libraries
+import warnings
+from ultralytics import YOLO  # Ensure ultralytics is installed
+from transformers import pipeline, DetrImageProcessor
+
+# Suppress unnecessary warnings
+warnings.filterwarnings("ignore", message=".*copying from a non-meta parameter.*")
+
+# Setup the image processor
+processor = DetrImageProcessor.from_pretrained("facebook/detr-resnet-50", use_fast=True)
+
+# Load the YOLO model (make sure ultralytics is installed)
+model = YOLO("yolov5s.pt")  # Change to the model you are using
+
+# Your model inference or other operations
+# Example detection function
+def detect_objects(image):
+    # Use your model for object detection
+    results = model(image)
+    return results
+
+# Call the function
+image = "path_to_image.jpg"  # Replace with your image path
+detection_results = detect_objects(image)
+print(detection_results)