Update app.py

app.py

@@ -45,7 +45,13 @@ def detect_objects(image):
     for i in range(predictions.shape[1]):  # 遍历每个预测
         score = predictions[0, i, -1].item()  # 假设最后一个维度是分数
         if score > confidence_threshold:  # 使用新的阈值过滤低置信度的预测
+            
             box = predictions[0, i, :-1].tolist()  # 获取边界框坐标（假设在前面）
+            box[0] *= original_image.width / 800  # 将坐标缩放回原始图像尺寸
+            box[1] *= original_image.height / 800
+            box[2] *= original_image.width / 800
+            box[3] *= original_image.height / 800
+            
             detections.append({
                 "label": f"Object {i}",  # 根据实际情况替换标签
                 "confidence": round(score, 3),
@@ -53,7 +59,8 @@ def detect_objects(image):
             })
             # 绘制边界框和标签到原始图像上
             draw = ImageDraw.Draw(original_image)
-            draw.rectangle(box, outline="red", width=3)  # 绘制矩形框
+            draw.rectangle(box[:4], outline="red", width=3)  # 绘制矩形框，确保只取前四个坐标
+            
             draw.text((box[0], box[1]), f"{detections[-1]['label']} ({detections[-1]['confidence']})", fill="red")  # 添加标签
 
     return original_image, detections