Update app.py

app.py

@@ -173,29 +173,34 @@ 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(hsv[:,:,2]))"] = hue_std / 180  # 归一化
-        features["saturation_variation"] =_variation"] = val_std /_final_decision(ai_probability, image率和图像特征做出更准确的决策础决策
+        val_std = float(np.std(hsvue_variation"] = hue_std / 180  # 归一化
+        features["saturation_variation"] = sat_std /  val_std / 255
+    
+    return 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 < 0.3:
-        base_decision = "高概率人类创 "无法确定"
+        base_decision = "高概率AI生成"
+    elif ai_probability < 0.3:
+        base_decision = "高概率人类创作"
     
-    整
-    feature_score = 0
     
-    # 检查对称性 - 高对称性通常表示AI" in image_features and image_features["horizontal_symmetry"] > 0.0.1
-    if "vertical_symmetry" in image_features and image_features["vertical_symmetry"] > 0. 0.1
+    # 特征调整
+    feature_score = 0
     
-    - AI生成图像通常边缘密度较低
-    if image_features["edge_density"] < 0.01
+    # 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
     
-    # 检查噪声 - AI生成图像通常噪声较低< 0.3:
+    # 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
     
-    # 检查颜色变化 - AI生成图像通常颜色变化ue_variation" in image_features and image_features["hue_variation"] < 0.1
-    if "saturation_variation" in image_features and image_features["saturation_variation"] 0.05
+    # 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
     
     # 调整最终概率
-    adjusted_probability = min(1.0, max(0.0, ai_probability + feature_score))新判断
+    adjusted_probability = min(1.0, max(0.0, ai_probability + feature_score)) 重新判断
     if adjusted_probability > 0.7:
         return "高概率AI生成", adjusted_probability
     elif adjusted_probability < 0.3:
@@ -278,4 +283,4 @@ iface = gr.Interface(
     allow_flagging="never"
 )
 
-iface.launch()
+iface.launch()