Update app.py

app.py

@@ -173,34 +173,33 @@ def analyze_image_features(image):
         hsv = cv2.cvtColor(img_cv, cv2.COLOR_BGR2HSV)
         hue_std = float(np.std(hsv[:,:,0]))
         sat_std = float(np.std(hsv[:,:,1]))
-        val_std = float(np.std(hsvue_variation"] = hue_std / 180  # 归一化
-        features["saturation_variation"] = sat_std /  val_std / 255
-    
-    return features
+        val_std = float(np.std(hsv[:,:,2ue_variation"] = hue 归一化
+        features["saturation_variation"] = sat_std / 255 val_std / features
 
-def make_final_decision(ai_probability, image_features):出更准确的决策"""
-    # 基础决策
-    if ai_probability > 0.7:
-        base_decision = "高概率AI生成"
-    elif ai_probability < 0.3:
-        base_decision = "高概率人类创作"
-    
+def make_final_decision(ai_probability, image于AI概率和图像特征做出更准 基础 ai_probability >_decision = "高概率AI生 < 0.3:
+        类创作"
+    else:
+        base_decision = "无法确定"
     
     # 特征调整
     feature_score = 0
     
-    # 检查对称性 - 高对称性通" in image_features and image_features["horizontal_score += 0.1
-    if "vertical_symmetry" in image_features and image_features["vertical_symmetry"] 0.1
+    # 检查对称性 - 高对称性通常表示AI生成
+    if "horizontal_symmetry" in image_features and image_features["horizontal_symmetry"]0.1
+    if "vertical_symmetry" in image_features and image_features["vertical_symmetry"] > 0.85:
+        
+    
+    # 检查边缘 - AI生成图像通常边缘密_density"] < 0.010.1
     
-    # 检查边缘 - AI生成图像通常边缘密度较低
-    if image_features["edge_density"] < 0.01 检查噪声 - AI生成图_features["noise_level"] < 0.3:
-        feature_score += 0.1
+    # 检查噪声 - AI生成图像通常噪声较低_level"] < 0.30.1
     
-    # 检查颜色变化 - AI生成图像通常颜色变化更平滑 and image_features["hue_variation"] < 0.05
-    if "saturation_variation" in image_features and image_features["saturation_variation"] < 0.1
+    # 检查颜色变化 - AI生成图像通常颜色变化更平滑 in image_features and image_features["hue_variation"] < 0.05
+    if "saturation_variation" in image_features and image_features["saturation_variation"] < 0.10.1
     
     # 调整最终概率
-    adjusted_probability = min(1.0, max(0.0, ai_probability + feature_score)) 重新判断
+    adjusted_probability = min(1.0, max(0.0, ai_probability + feature_score))
+    
+    断
     if adjusted_probability > 0.7:
         return "高概率AI生成", adjusted_probability
     elif adjusted_probability < 0.3:
@@ -283,4 +282,4 @@ iface = gr.Interface(
     allow_flagging="never"
 )
 
-iface.launch()
+iface.launch()