feat: 降低 NSFW 检测阈值，显示更多检测结果

internal/nsfw/server.py

@@ -22,17 +22,17 @@ import json
 import os
 import shutil
 import sys
-import tempfile
 import threading
 import urllib.request
 from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
 
+import cv2
+import numpy as np
 from nudenet import NudeDetector
+from nudenet.nudenet import _read_image
 
 # 只报 OpenCV 致命错误，别让 imread 的 WARN 刷屏（也避免误导排查）
 try:
-    import cv2
-
     cv2.setLogLevel(8)  # LOG_LEVEL_ERROR
 except Exception:
     pass
@@ -145,6 +145,74 @@ def _new_detector():
         return NudeDetector()
 
 
+def _raw_detect(det, data):
+    """直接调用 ONNX 推理，用 0.05 低阈值后处理（NudeNet 内置的 detect 用 0.2 太严格）。
+
+    绕过 NudeDetector.detect() 的硬编码 0.2 阈值，让低置信度的检测结果也能返回，
+    最终判定交给 Go 侧的用户配置阈值。
+    """
+    mat = cv2.imdecode(np.frombuffer(data, np.uint8), -1)
+    if mat is None:
+        raise OSError("图片解码失败")
+
+    mat_c3 = cv2.cvtColor(mat, cv2.COLOR_RGBA2BGR)
+    ow, oh = mat_c3.shape[1], mat_c3.shape[0]
+    max_size = max(ow, oh)
+    x_pad = max_size - ow
+    y_pad = max_size - oh
+    x_ratio = max_size / ow
+    y_ratio = max_size / oh
+
+    mat_pad = cv2.copyMakeBorder(mat_c3, 0, y_pad, 0, x_pad, cv2.BORDER_CONSTANT)
+    blob = cv2.dnn.blobFromImage(mat_pad, 1 / 255.0, (det.input_width, det.input_height), (0, 0, 0), swapRB=True, crop=False)
+
+    outputs = det.onnx_session.run(None, {det.input_name: blob})
+    outs = np.transpose(np.squeeze(outputs[0]))
+    rows = outs.shape[0]
+
+    boxes, scores, class_ids = [], [], []
+    for i in range(rows):
+        cls_scores = outs[i][4:]
+        max_score = np.amax(cls_scores)
+        if max_score >= 0.05:  # 低阈值：NudeNet 内置是 0.2，这里降到 0.05
+            class_id = int(np.argmax(cls_scores))
+            x, y, w, h = outs[i][0:4]
+            x, y = x - w / 2, y - h / 2
+            w_ = w * (ow + x_pad) / det.input_width
+            h_ = h * (oh + y_pad) / det.input_height
+            x = x * (ow + x_pad) / det.input_width
+            y = y * (oh + y_pad) / det.input_height
+            x, y = max(0, min(x, ow)), max(0, min(y, oh))
+            w_ = min(w_, ow - x)
+            h_ = min(h_, oh - y)
+            boxes.append([x, y, w_, h_])
+            scores.append(float(max_score))
+            class_ids.append(class_id)
+
+    indices = cv2.dnn.NMSBoxes(boxes, scores, 0.1, 0.45)
+
+    detections = []
+    for i in indices:
+        idx = i if isinstance(i, int) else i[0]
+        detections.append({
+            "class": __labels[class_ids[idx]],
+            "score": scores[idx],
+            "box": [int(boxes[idx][0]), int(boxes[idx][1]), int(boxes[idx][2]), int(boxes[idx][3])],
+        })
+    return detections
+
+
+# NudeNet 的标签表（和 nudenet.nudenet.__labels 一致）
+__labels = [
+    "FEMALE_GENITALIA_COVERED", "FACE_FEMALE", "BUTTOCKS_EXPOSED",
+    "FEMALE_BREAST_EXPOSED", "FEMALE_GENITALIA_EXPOSED", "MALE_BREAST_EXPOSED",
+    "ANUS_EXPOSED", "FEET_EXPOSED", "BELLY_COVERED", "FEET_COVERED",
+    "ARMPITS_COVERED", "ARMPITS_EXPOSED", "FACE_MALE", "BELLY_EXPOSED",
+    "MALE_GENITALIA_EXPOSED", "ANUS_COVERED", "FEMALE_BREAST_COVERED",
+    "BUTTOCKS_COVERED",
+]
+
+
 def _longpath(path):
     """Windows 下给绝对路径加 \\\\?\\ 前缀，让 Python 原生 open 也能处理超长路径。"""
     if os.name != "nt":
@@ -171,39 +239,17 @@ def _read_bytes(path):
     return data
 
 
-def _detect_bytes(det, data, path):
-    """把图片字节喂给 NudeNet。v3 直接吃 bytes；老版 v2 只收路径时落到临时短路径重试。
-
-    用线程自己的检测器实例推理，各实例互不干扰，可以真·并行。
-    """
-    try:
-        return det.detect(data)
-    except (TypeError, AttributeError):
-        tmp = None
-        try:
-            fd, tmp = tempfile.mkstemp(suffix=os.path.splitext(path)[1] or ".jpg")
-            with os.fdopen(fd, "wb") as f:
-                f.write(data)
-            return det.detect(tmp)
-        finally:
-            if tmp:
-                try:
-                    os.unlink(tmp)
-                except OSError:
-                    pass
-
-
 def _infer(path):
     """整个推理任务（读文件 + 检测），提交到固定线程池执行。
 
-    读文件在池外并行进行；推理用线程各自的独立检测器，N 个 worker 真·并行。
+    使用 _raw_detect 绕过 NudeNet 内置的 0.2 阈值，用 0.05 低阈值返回更多结果。
     """
     data = _read_bytes(path)
     det = getattr(_thread_local, "detector", None)
     if det is None:
         det = _new_detector()
         _thread_local.detector = det
-    return _detect_bytes(det, data, path)
+    return _raw_detect(det, data)
 
 
 class Handler(BaseHTTPRequestHandler):