Update app.py

app.py

@@ -2,7 +2,7 @@ import supervision as sv
 import gradio as gr
 from ultralytics import YOLO
 import sahi
-
+import numpy as np
 
 
 
@@ -28,19 +28,20 @@ annotatorbbox = sv.BoxAnnotator()
 annotatormask=sv.MaskAnnotator()
 model = YOLO("best_Receipt.pt")
 
+
 def yolov8_inference(
     image: gr.inputs.Image = None,
-    model_name: gr.inputs.Dropdown = None,
-    image_size: gr.inputs.Slider = 320,
-    conf_threshold: gr.inputs.Slider = 0.25,
+    conf_threshold: gr.inputs.Slider = 0.5,
     iou_threshold: gr.inputs.Slider = 0.45,
 ):
 
-    
-    results = model(image,conf=conf_threshold,iou=iou_threshold ,imgsz=320)[0]
+    image=image[:, :, ::-1].astype(np.uint8)
+    model = YOLO("https://huggingface.co/spaces/devisionx/first-demo/blob/main/best_Receipt.pt")
+    results = model(image,imgsz=320)[0]
+    image=image[:, :, ::-1].astype(np.uint8)
     detections = sv.Detections.from_yolov8(results)
-    annotated_image = annotatorbbox.annotate(scene=image, detections=detections)
-    annotated_image = annotatormask.annotate(scene=annotated_image, detections=detections)
+    annotated_image = annotatormask.annotate(scene=image, detections=detections)
+    annotated_image = annotatorbbox.annotate(scene=annotated_image , detections=detections)