From 34cbeb69c3182266d24caf4f782b264206ba2ba3 Mon Sep 17 00:00:00 2001 From: quant Date: Wed, 18 Feb 2026 00:55:37 +0800 Subject: [PATCH] admin update --- fastAPI_tarot.py | 196 ++++++++++++++++++++++++++++------------------ history.json | 0 static/admin.html | 137 +++++++++++++++++++++++--------- 3 files changed, 217 insertions(+), 116 deletions(-) create mode 100644 history.json diff --git a/fastAPI_tarot.py b/fastAPI_tarot.py index 2d90683..6d80556 100644 --- a/fastAPI_tarot.py +++ b/fastAPI_tarot.py @@ -266,7 +266,7 @@ def is_english(text: str) -> bool: return False return True -def append_to_history(req_type: str, prompt: str, status: str, result_path: str = None, details: str = ""): +def append_to_history(req_type: str, prompt: str, status: str, result_path: str = None, details: str = "", final_prompt: str = None, duration: float = 0.0): """ 记录请求历史到 history.json """ @@ -274,9 +274,11 @@ def append_to_history(req_type: str, prompt: str, status: str, result_path: str "timestamp": time.time(), "type": req_type, "prompt": prompt, + "final_prompt": final_prompt, "status": status, "result_path": result_path, - "details": details + "details": details, + "duration": duration } try: with open(HISTORY_FILE, "a", encoding="utf-8") as f: @@ -371,7 +373,7 @@ def load_image_from_url(url: str) -> Image.Image: except Exception as e: raise HTTPException(status_code=400, detail=f"无法下载图片: {str(e)}") -def crop_and_save_objects(image: Image.Image, masks, boxes, output_dir: str = RESULT_IMAGE_DIR, is_tarot: bool = True, cutout: bool = False) -> list[dict]: +def crop_and_save_objects(image: Image.Image, masks, boxes, output_dir: str = RESULT_IMAGE_DIR, is_tarot: bool = True, cutout: bool = False, perspective_correction: bool = False) -> list[dict]: """ 根据 mask 和 box 进行处理并保存独立的对象图片 @@ -382,6 +384,7 @@ def crop_and_save_objects(image: Image.Image, masks, boxes, output_dir: str = RE - output_dir: 输出目录 - is_tarot: 是否为塔罗牌模式 (会影响文件名前缀和旋转逻辑) - cutout: 如果为 True，则进行轮廓抠图（透明背景）；否则进行透视矫正（主要用于卡片） + - perspective_correction: 是否进行梯度透视矫正 返回: - 保存的对象信息列表 @@ -409,8 +412,8 @@ def crop_and_save_objects(image: Image.Image, masks, boxes, output_dir: str = RE else: mask_uint8 = (mask_np > 0.5).astype(np.uint8) * 255 + # --- 准备基础图像 --- if cutout: - # --- 轮廓抠图模式 (透明背景) --- # 1. 准备 RGBA 原图 if image.mode != "RGBA": img_rgba = image.convert("RGBA") @@ -421,73 +424,84 @@ def crop_and_save_objects(image: Image.Image, masks, boxes, output_dir: str = RE mask_img = Image.fromarray(mask_uint8, mode='L') # 3. 将 Mask 应用到 Alpha 通道 - cutout_img = Image.new("RGBA", img_rgba.size, (0, 0, 0, 0)) - cutout_img.paste(image.convert("RGB"), (0, 0), mask=mask_img) + base_img_pil = Image.new("RGBA", img_rgba.size, (0, 0, 0, 0)) + base_img_pil.paste(image.convert("RGB"), (0, 0), mask=mask_img) - # 4. Crop to Box - x1, y1, x2, y2 = map(int, box_np) - w, h = cutout_img.size - x1 = max(0, x1); y1 = max(0, y1) - x2 = min(w, x2); y2 = min(h, y2) - - if x2 > x1 and y2 > y1: - final_img = cutout_img.crop((x1, y1, x2, y2)) - else: - final_img = cutout_img # Fallback - - # Save - prefix = "cutout" - is_rotated = False - - filename = f"{prefix}_{uuid.uuid4().hex}_{i}.png" - save_path = os.path.join(output_dir, filename) - final_img.save(save_path) - - saved_objects.append({ - "filename": filename, - "is_rotated_by_algorithm": is_rotated, - "note": "Mask cutout applied. Background removed." - }) - + # Convert to numpy for potential warping + base_img_arr = np.array(base_img_pil) else: + base_img_pil = image.convert("RGB") + base_img_arr = img_arr # RGB numpy array + + # --- 透视矫正 vs 简单裁剪 --- + final_img_pil = None + is_rotated = False + note = "" + + if perspective_correction: # --- 透视矫正模式 (矩形矫正) --- contours, _ = cv2.findContours(mask_uint8, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) - if not contours: - continue - - c = max(contours, key=cv2.contourArea) - peri = cv2.arcLength(c, True) - approx = cv2.approxPolyDP(c, 0.04 * peri, True) - if len(approx) == 4: - pts = approx.reshape(4, 2) + pts = None + if contours: + c = max(contours, key=cv2.contourArea) + peri = cv2.arcLength(c, True) + approx = cv2.approxPolyDP(c, 0.04 * peri, True) + + if len(approx) == 4: + pts = approx.reshape(4, 2) + else: + rect = cv2.minAreaRect(c) + pts = cv2.boxPoints(rect) + + if pts is not None: + warped = four_point_transform(base_img_arr, pts) + note = "Geometric correction applied." else: - rect = cv2.minAreaRect(c) - pts = cv2.boxPoints(rect) - - warped = four_point_transform(img_arr, pts) - - # Check orientation (Portrait vs Landscape) + # Fallback to simple crop if no contours found + x1, y1, x2, y2 = map(int, box_np) + # Ensure bounds + h, w = base_img_arr.shape[:2] + x1 = max(0, x1); y1 = max(0, y1) + x2 = min(w, x2); y2 = min(h, y2) + warped = base_img_arr[y1:y2, x1:x2] + note = "Correction failed, fallback to crop." + + # Check orientation (Portrait vs Landscape) - Only for Tarot usually h, w = warped.shape[:2] - is_rotated = False # 强制竖屏逻辑 (塔罗牌通常是竖屏) if is_tarot and w > h: warped = cv2.rotate(warped, cv2.ROTATE_90_CLOCKWISE) is_rotated = True - pil_warped = Image.fromarray(warped) + final_img_pil = Image.fromarray(warped) - prefix = "tarot" if is_tarot else "segment" - filename = f"{prefix}_{uuid.uuid4().hex}_{i}.png" - save_path = os.path.join(output_dir, filename) - pil_warped.save(save_path) + else: + # --- 简单裁剪模式 (Simple Crop) --- + x1, y1, x2, y2 = map(int, box_np) + w, h = base_img_pil.size + x1 = max(0, x1); y1 = max(0, y1) + x2 = min(w, x2); y2 = min(h, y2) - saved_objects.append({ - "filename": filename, - "is_rotated_by_algorithm": is_rotated, - "note": "Geometric correction applied." - }) + if x2 > x1 and y2 > y1: + final_img_pil = base_img_pil.crop((x1, y1, x2, y2)) + else: + final_img_pil = base_img_pil # Fallback + + note = "Simple crop applied." + + # --- 保存图片 --- + prefix = "cutout" if cutout else ("tarot" if is_tarot else "segment") + filename = f"{prefix}_{uuid.uuid4().hex}_{i}.png" + save_path = os.path.join(output_dir, filename) + final_img_pil.save(save_path) + + saved_objects.append({ + "filename": filename, + "is_rotated_by_algorithm": is_rotated, + "note": note + }) return saved_objects @@ -660,6 +674,7 @@ async def segment( image_url: Optional[str] = Form(None, description="URL of the image"), save_segment_images: bool = Form(False, description="Whether to save and return individual segmented objects"), cutout: bool = Form(False, description="If True, returns transparent background PNGs; otherwise returns original crops"), + perspective_correction: bool = Form(False, description="If True, applies perspective correction (warping) to the segmented object."), highlight: bool = Form(False, description="If True, darkens the background to highlight the subject (周边变黑放大)."), confidence: float = Form(0.7, description="Confidence threshold (0.0-1.0). Default is 0.7.") @@ -671,11 +686,13 @@ async def segment( - 支持自动将中文 Prompt 翻译为英文 - 支持周边变黑放大效果 (Highlight Mode) - 支持手动设置置信度 (Confidence Threshold) + - 支持透视矫正 (Perspective Correction) """ if not file and not image_url: raise HTTPException(status_code=400, detail="必须提供 file (图片文件) 或 image_url (图片链接)") + start_time = time.time() # 1. Prompt 处理 final_prompt = prompt if not is_english(prompt): @@ -695,7 +712,8 @@ async def segment( elif image_url: image = load_image_from_url(image_url) except Exception as e: - append_to_history("general", prompt, "failed", details=f"Image Load Error: {str(e)}") + duration = time.time() - start_time + append_to_history("general", prompt, "failed", details=f"Image Load Error: {str(e)}", final_prompt=final_prompt, duration=duration) raise HTTPException(status_code=400, detail=f"图片解析失败: {str(e)}") processor = request.app.state.processor @@ -725,7 +743,8 @@ async def segment( processor.confidence_threshold = original_confidence except Exception as e: - append_to_history("general", prompt, "failed", details=f"Inference Error: {str(e)}") + duration = time.time() - start_time + append_to_history("general", prompt, "failed", details=f"Inference Error: {str(e)}", final_prompt=final_prompt, duration=duration) raise HTTPException(status_code=500, detail=f"模型推理错误: {str(e)}") # 4. 结果可视化与保存 @@ -738,7 +757,8 @@ async def segment( else: filename = generate_and_save_result(image, inference_state) except Exception as e: - append_to_history("general", prompt, "failed", details=f"Save Error: {str(e)}") + duration = time.time() - start_time + append_to_history("general", prompt, "failed", details=f"Save Error: {str(e)}", final_prompt=final_prompt, duration=duration) raise HTTPException(status_code=500, detail=f"绘图保存错误: {str(e)}") file_url = request.url_for("static", path=f"results/{filename}") @@ -757,7 +777,8 @@ async def segment( boxes, output_dir=output_dir, is_tarot=False, - cutout=cutout + cutout=cutout, + perspective_correction=perspective_correction ) for obj in saved_objects: @@ -771,7 +792,8 @@ async def segment( except Exception as e: print(f"Error saving segments: {e}") # Don't fail the whole request just for this part, but log it? Or fail? Usually fail. - append_to_history("general", prompt, "partial_success", result_path=f"results/{filename}", details="Segments save failed") + duration = time.time() - start_time + append_to_history("general", prompt, "partial_success", result_path=f"results/{filename}", details="Segments save failed", final_prompt=final_prompt, duration=duration) raise HTTPException(status_code=500, detail=f"保存分割图片失败: {str(e)}") response_content = { @@ -784,7 +806,8 @@ async def segment( if save_segment_images: response_content["segmented_images"] = saved_segments_info - append_to_history("general", prompt, "success", result_path=f"results/{filename}", details=f"Detected: {len(masks)}") + duration = time.time() - start_time + append_to_history("general", prompt, "success", result_path=f"results/{filename}", details=f"Detected: {len(masks)}", final_prompt=final_prompt, duration=duration) return JSONResponse(content=response_content) # ------------------------------------------ @@ -808,13 +831,15 @@ async def segment_tarot( if not file and not image_url: raise HTTPException(status_code=400, detail="必须提供 file (图片文件) 或 image_url (图片链接)") + start_time = time.time() try: if file: image = Image.open(file.file).convert("RGB") elif image_url: image = load_image_from_url(image_url) except Exception as e: - append_to_history("tarot", f"expected: {expected_count}", "failed", details=f"Image Load Error: {str(e)}") + duration = time.time() - start_time + append_to_history("tarot", f"expected: {expected_count}", "failed", details=f"Image Load Error: {str(e)}", duration=duration) raise HTTPException(status_code=400, detail=f"图片解析失败: {str(e)}") processor = request.app.state.processor @@ -825,7 +850,8 @@ async def segment_tarot( output = processor.set_text_prompt(state=inference_state, prompt="tarot card") masks, boxes, scores = output["masks"], output["boxes"], output["scores"] except Exception as e: - append_to_history("tarot", f"expected: {expected_count}", "failed", details=f"Inference Error: {str(e)}") + duration = time.time() - start_time + append_to_history("tarot", f"expected: {expected_count}", "failed", details=f"Inference Error: {str(e)}", duration=duration) raise HTTPException(status_code=500, detail=f"模型推理错误: {str(e)}") # 核心逻辑：判断数量 @@ -844,7 +870,8 @@ async def segment_tarot( except: file_url = None - append_to_history("tarot", f"expected: {expected_count}", "failed", result_path=f"results/{request_id}/{filename}" if file_url else None, details=f"Detected {detected_count} cards, expected {expected_count}") + duration = time.time() - start_time + append_to_history("tarot", f"expected: {expected_count}", "failed", result_path=f"results/{request_id}/{filename}" if file_url else None, details=f"Detected {detected_count} cards, expected {expected_count}", duration=duration) return JSONResponse( status_code=400, content={ @@ -857,9 +884,10 @@ async def segment_tarot( # 数量正确，执行抠图 try: - saved_objects = crop_and_save_objects(image, masks, boxes, output_dir=output_dir) + saved_objects = crop_and_save_objects(image, masks, boxes, output_dir=output_dir, is_tarot=True, perspective_correction=True) except Exception as e: - append_to_history("tarot", f"expected: {expected_count}", "failed", details=f"Crop Error: {str(e)}") + duration = time.time() - start_time + append_to_history("tarot", f"expected: {expected_count}", "failed", details=f"Crop Error: {str(e)}", duration=duration) raise HTTPException(status_code=500, detail=f"抠图处理错误: {str(e)}") # 生成 URL 列表和元数据 @@ -881,7 +909,8 @@ async def segment_tarot( except: main_file_url = None - append_to_history("tarot", f"expected: {expected_count}", "success", result_path=f"results/{request_id}/{main_filename}" if main_file_url else None, details=f"Successfully segmented {expected_count} cards") + duration = time.time() - start_time + append_to_history("tarot", f"expected: {expected_count}", "success", result_path=f"results/{request_id}/{main_filename}" if main_file_url else None, details=f"Successfully segmented {expected_count} cards", duration=duration) return JSONResponse(content={ "status": "success", "message": f"成功识别并分割 {expected_count} 张塔罗牌 (已执行透视矫正)", @@ -907,13 +936,15 @@ async def recognize_tarot( if not file and not image_url: raise HTTPException(status_code=400, detail="必须提供 file (图片文件) 或 image_url (图片链接)") + start_time = time.time() try: if file: image = Image.open(file.file).convert("RGB") elif image_url: image = load_image_from_url(image_url) except Exception as e: - append_to_history("tarot-recognize", f"expected: {expected_count}", "failed", details=f"Image Load Error: {str(e)}") + duration = time.time() - start_time + append_to_history("tarot-recognize", f"expected: {expected_count}", "failed", details=f"Image Load Error: {str(e)}", duration=duration) raise HTTPException(status_code=400, detail=f"图片解析失败: {str(e)}") processor = request.app.state.processor @@ -923,7 +954,8 @@ async def recognize_tarot( output = processor.set_text_prompt(state=inference_state, prompt="tarot card") masks, boxes, scores = output["masks"], output["boxes"], output["scores"] except Exception as e: - append_to_history("tarot-recognize", f"expected: {expected_count}", "failed", details=f"Inference Error: {str(e)}") + duration = time.time() - start_time + append_to_history("tarot-recognize", f"expected: {expected_count}", "failed", details=f"Inference Error: {str(e)}", duration=duration) raise HTTPException(status_code=500, detail=f"模型推理错误: {str(e)}") detected_count = len(masks) @@ -951,7 +983,8 @@ async def recognize_tarot( spread_info = recognize_spread_with_qwen(temp_raw_path) if detected_count != expected_count: - append_to_history("tarot-recognize", f"expected: {expected_count}", "failed", result_path=f"results/{request_id}/{main_filename}" if main_file_url else None, details=f"Detected {detected_count}, expected {expected_count}") + duration = time.time() - start_time + append_to_history("tarot-recognize", f"expected: {expected_count}", "failed", result_path=f"results/{request_id}/{main_filename}" if main_file_url else None, details=f"Detected {detected_count}, expected {expected_count}", duration=duration) return JSONResponse( status_code=400, content={ @@ -965,9 +998,10 @@ async def recognize_tarot( # 数量正确，执行抠图 + 矫正 try: - saved_objects = crop_and_save_objects(image, masks, boxes, output_dir=output_dir) + saved_objects = crop_and_save_objects(image, masks, boxes, output_dir=output_dir, is_tarot=True, perspective_correction=True) except Exception as e: - append_to_history("tarot-recognize", f"expected: {expected_count}", "failed", details=f"Crop Error: {str(e)}") + duration = time.time() - start_time + append_to_history("tarot-recognize", f"expected: {expected_count}", "failed", details=f"Crop Error: {str(e)}", duration=duration) raise HTTPException(status_code=500, detail=f"抠图处理错误: {str(e)}") # 遍历每张卡片进行识别 @@ -988,7 +1022,8 @@ async def recognize_tarot( "note": obj["note"] }) - append_to_history("tarot-recognize", f"expected: {expected_count}", "success", result_path=f"results/{request_id}/{main_filename}" if main_file_url else None, details=f"Spread: {spread_info.get('spread_name', 'Unknown')}") + duration = time.time() - start_time + append_to_history("tarot-recognize", f"expected: {expected_count}", "success", result_path=f"results/{request_id}/{main_filename}" if main_file_url else None, details=f"Spread: {spread_info.get('spread_name', 'Unknown')}", duration=duration) return JSONResponse(content={ "status": "success", "message": f"成功识别并分割 {expected_count} 张塔罗牌 (含Qwen识别结果)", @@ -1019,6 +1054,7 @@ async def segment_face( if not file and not image_url: raise HTTPException(status_code=400, detail="必须提供 file (图片文件) 或 image_url (图片链接)") + start_time = time.time() # Prompt 翻译/优化 final_prompt = prompt if not is_english(prompt): @@ -1038,7 +1074,8 @@ async def segment_face( elif image_url: image = load_image_from_url(image_url) except Exception as e: - append_to_history("face", prompt, "failed", details=f"Image Load Error: {str(e)}") + duration = time.time() - start_time + append_to_history("face", prompt, "failed", details=f"Image Load Error: {str(e)}", final_prompt=final_prompt, duration=duration) raise HTTPException(status_code=400, detail=f"图片解析失败: {str(e)}") processor = request.app.state.processor @@ -1056,7 +1093,8 @@ async def segment_face( except Exception as e: import traceback traceback.print_exc() - append_to_history("face", prompt, "failed", details=f"Process Error: {str(e)}") + duration = time.time() - start_time + append_to_history("face", prompt, "failed", details=f"Process Error: {str(e)}", final_prompt=final_prompt, duration=duration) raise HTTPException(status_code=500, detail=f"处理失败: {str(e)}") # 补全 URL @@ -1069,7 +1107,8 @@ async def segment_face( relative_path = item.pop("relative_path") item["url"] = str(request.url_for("static", path=relative_path)) - append_to_history("face", prompt, result["status"], details=f"Results: {len(result.get('results', []))}") + duration = time.time() - start_time + append_to_history("face", prompt, result["status"], details=f"Results: {len(result.get('results', []))}", final_prompt=final_prompt, duration=duration) return JSONResponse(content=result) # ========================================== @@ -1168,6 +1207,9 @@ async def list_files(path: str = ""): # path is relative to results/ # so url is /static/results/path/name rel_path = os.path.join("results", path, entry.name) + # Ensure forward slashes for URL + if os.sep != "/": + rel_path = rel_path.replace(os.sep, "/") item["url"] = f"/static/{rel_path}" items.append(item) diff --git a/history.json b/history.json new file mode 100644 index 0000000..e69de29 diff --git a/static/admin.html b/static/admin.html index 0499538..c9a987c 100644 --- a/static/admin.html +++ b/static/admin.html @@ -65,58 +65,91 @@
-

最近识别记录

+

+ 最近识别记录 + +

-
+
- - - - - + + + + + + - - + - - - + - -
时间类型Prompt / 详情状态操作时间类型Prompt / 详情耗时状态查看
- {{ formatDate(record.timestamp) }} +
+
{{ formatDate(record.timestamp).split(' ')[0] }}
+
{{ formatDate(record.timestamp).split(' ')[1] }}
 - + + {{ record.type }} - {{ record.details }} + +
+ +
+ + {{ record.prompt }} +
+ + +
+ + {{ record.final_prompt }} +
+ + +
+ + {{ record.details }} +
+
- + +
+ {{ record.duration.toFixed(2) }}s +
+
-
+ 		+ + {{ record.status }} - + + + +
- 暂无记录 + +
+ + 暂无记录 +
-
- -
@@ -145,7 +178,7 @@ {{ file.count }} 项
-
+
{{ file.name }}
@@ -456,17 +489,36 @@ }; const viewResult = (path) => { - // path like "results/..." - // We need to parse this. If it's a directory, go to files tab. If image, preview. - // For simplicity, let's assume it links to the folder in files tab + // path format: "results/subdir/file.jpg" or "results/file.jpg" currentTab.value = 'files'; - // Extract folder name from path if possible, or just go to root - const match = path.match(/results\/([^\/]+)/); - if (match) { - currentPath.value = match[1]; + + // Remove "results/" prefix + // Note: path usually comes from backend as "results/..." + let relativePath = path; + if (relativePath.startsWith('results/')) { + relativePath = relativePath.substring(8); // Remove "results/" + } + + // Check if it looks like a file (has extension) + const isFile = /\.[a-zA-Z0-9]+$/.test(relativePath); + + if (isFile) { + // It's a file + const lastSlashIndex = relativePath.lastIndexOf('/'); + let dirPath = ''; + + if (lastSlashIndex !== -1) { + dirPath = relativePath.substring(0, lastSlashIndex); + } + + currentPath.value = dirPath; fetchFiles(); + + // Show preview immediately + previewUrl.value = '/static/' + path; } else { - currentPath.value = ''; + // It's likely a directory + currentPath.value = relativePath; fetchFiles(); } }; @@ -483,11 +535,18 @@ return new Date(ts * 1000).toLocaleString(); }; + const getDurationClass = (duration) => { + if (duration < 2.0) return 'text-green-600 bg-green-50'; + if (duration < 5.0) return 'text-yellow-600 bg-yellow-50'; + return 'text-red-600 bg-red-50'; + }; + const getTypeBadgeClass = (type) => { const map = { - 'general': 'bg-blue-100 text-blue-800', - 'tarot': 'bg-purple-100 text-purple-800', - 'face': 'bg-pink-100 text-pink-800' + 'general': 'bg-blue-50 text-blue-600 border border-blue-100', + 'tarot': 'bg-purple-50 text-purple-600 border border-purple-100', + 'tarot-recognize': 'bg-indigo-50 text-indigo-600 border border-indigo-100', + 'face': 'bg-pink-50 text-pink-600 border border-pink-100' }; return map[type] || 'bg-gray-100 text-gray-800'; }; @@ -508,7 +567,7 @@ currentTab, history, files, currentPath, enterDir, navigateUp, deleteFile, triggerCleanup, viewResult, previewImage, isImage, previewUrl, - formatDate, getTypeBadgeClass, cleaning, deviceInfo, + formatDate, getDurationClass, getTypeBadgeClass, cleaning, deviceInfo, currentModel, availableModels, updateModel, cleanupConfig, saveCleanupConfig, prompts, fetchPrompts, savePrompt, getPromptDescription