Update app.py

app.py

@@ -1,9 +1,11 @@
 import PIL.Image as Image
 import gradio as gr
+
 from ultralytics import ASSETS, YOLO
 
 model = YOLO("./best.pt")
 
+
 def predict_image(img, conf_threshold, iou_threshold):
     results = model.predict(
         source=img,
@@ -14,41 +16,28 @@ def predict_image(img, conf_threshold, iou_threshold):
         imgsz=640,
     )
 
-    # Filter out results with confidence equal to 0
-    results = [r for r in results if r["conf"] > 0]
-
-    if results:
-        # Take the result with the highest confidence
-        result = max(results, key=lambda x: x["conf"])
-
-        # Extract box, label, and highest probability
-        box = result["xyxy"][0]
-        label = result["label"][0]
-        confidence = result["conf"]
-
-        # Return the box, label, and highest probability
-        return {
-            "box": box,
-            "label": label,
-            "confidence": confidence
-        }
-    else:
-        # No bounding box found
-        return {"box": [], "label": "No detection", "confidence": 0.0}
+    for r in results:
+        im_array = r.plot()
+        im = Image.fromarray(im_array[..., ::-1])
 
+    return im
 
 
 iface = gr.Interface(
     fn=predict_image,
     inputs=[
-        gr.Image(type="pil", label="Carregar Imagem"),
-        gr.Slider(minimum=0, maximum=1, value=0.25, label="Limiar de Confiança"),
-        gr.Slider(minimum=0, maximum=1, value=0.45, label="Limiar de IoU")
+        gr.Image(type="pil", label="Upload Image"),
+        gr.Slider(minimum=0, maximum=1, value=0.25, label="Confidence threshold"),
+        gr.Slider(minimum=0, maximum=1, value=0.45, label="IoU threshold")
     ],
-    outputs=gr.Image(type="pil", label="Resultado"),
-    title="Projeto de Visão Computacional para Fibromas Uterinos",
-    description="Carregue imagens para inferência."
+    outputs=gr.Image(type="pil", label="Result"),
+    title="Ultralytics Gradio",
+    description="Upload images for inference. The Ultralytics YOLOv8n model is used by default.",
+    examples=[
+        [ASSETS / "bus.jpg", 0.25, 0.45],
+        [ASSETS / "zidane.jpg", 0.25, 0.45],
+    ]
 )
 
 if __name__ == '__main__':
-    iface.launch()
+    iface.launch()