├── .gitignore ├── IMG_3895.jpeg ├── IMG_3895.png ├── LICENSE ├── README.md ├── base.jpg ├── docs ├── 12caad0293628ecba879cd580924a107.webp └── 924c5d89cc5badfce0f16963e649b6db.webp └── src ├── camera.py ├── detector └── sift.py └── main.py /.gitignore: -------------------------------------------------------------------------------- 1 | # Editors 2 | .vscode/ 3 | .idea/ 4 | 5 | # Vagrant 6 | .vagrant/ 7 | 8 | # Mac/OSX 9 | .DS_Store 10 | 11 | # Windows 12 | Thumbs.db 13 | 14 | # Source for the following rules: https://raw.githubusercontent.com/github/gitignore/master/Python.gitignore 15 | # Byte-compiled / optimized / DLL files 16 | __pycache__/ 17 | *.py[cod] 18 | *$py.class 19 | 20 | # C extensions 21 | *.so 22 | 23 | # Distribution / packaging 24 | .Python 25 | build/ 26 | develop-eggs/ 27 | dist/ 28 | downloads/ 29 | eggs/ 30 | .eggs/ 31 | lib/ 32 | lib64/ 33 | parts/ 34 | sdist/ 35 | var/ 36 | wheels/ 37 | *.egg-info/ 38 | .installed.cfg 39 | *.egg 40 | MANIFEST 41 | 42 | # PyInstaller 43 | # Usually these files are written by a python script from a template 44 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 45 | *.manifest 46 | *.spec 47 | 48 | # Installer logs 49 | pip-log.txt 50 | pip-delete-this-directory.txt 51 | 52 | # Unit test / coverage reports 53 | htmlcov/ 54 | .tox/ 55 | .nox/ 56 | .coverage 57 | .coverage.* 58 | .cache 59 | nosetests.xml 60 | coverage.xml 61 | *.cover 62 | .hypothesis/ 63 | .pytest_cache/ 64 | 65 | # Translations 66 | *.mo 67 | *.pot 68 | 69 | # Django stuff: 70 | *.log 71 | local_settings.py 72 | db.sqlite3 73 | 74 | # Flask stuff: 75 | instance/ 76 | .webassets-cache 77 | 78 | # Scrapy stuff: 79 | .scrapy 80 | 81 | # Sphinx documentation 82 | docs/_build/ 83 | 84 | # PyBuilder 85 | target/ 86 | 87 | # Jupyter Notebook 88 | .ipynb_checkpoints 89 | 90 | # IPython 91 | profile_default/ 92 | ipython_config.py 93 | 94 | # pyenv 95 | .python-version 96 | 97 | # celery beat schedule file 98 | celerybeat-schedule 99 | 100 | # SageMath parsed files 101 | *.sage.py 102 | 103 | # Environments 104 | .env 105 | .venv 106 | env/ 107 | venv/ 108 | ENV/ 109 | env.bak/ 110 | venv.bak/ 111 | 112 | # Spyder project settings 113 | .spyderproject 114 | .spyproject 115 | 116 | # Rope project settings 117 | .ropeproject 118 | 119 | # mkdocs documentation 120 | /site 121 | 122 | # mypy 123 | .mypy_cache/ 124 | .dmypy.json 125 | dmypy.json 126 | 127 | # Microsoft Office Temp Files 128 | ~$* 129 | -------------------------------------------------------------------------------- /IMG_3895.jpeg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ddrpa/jigsight/ec854fb4f180bec4d529f53eeebeeff02dc67817/IMG_3895.jpeg -------------------------------------------------------------------------------- /IMG_3895.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ddrpa/jigsight/ec854fb4f180bec4d529f53eeebeeff02dc67817/IMG_3895.png -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | 2 | Apache License 3 | Version 2.0, January 2004 4 | http://www.apache.org/licenses/ 5 | 6 | TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 7 | 8 | 1. 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We also recommend that a 186 | file or class name and description of purpose be included on the 187 | same "printed page" as the copyright notice for easier 188 | identification within third-party archives. 189 | 190 | Copyright [yyyy] [name of copyright owner] 191 | 192 | Licensed under the Apache License, Version 2.0 (the "License"); 193 | you may not use this file except in compliance with the License. 194 | You may obtain a copy of the License at 195 | 196 | http://www.apache.org/licenses/LICENSE-2.0 197 | 198 | Unless required by applicable law or agreed to in writing, software 199 | distributed under the License is distributed on an "AS IS" BASIS, 200 | WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 201 | See the License for the specific language governing permissions and 202 | limitations under the License. 203 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # JigSight 拼图辅助 2 | 3 | 基于计算机视觉的拼图辅助系统，帮助用户快速找到拼图碎片在原图中的位置和正确的旋转角度。 4 | 5 | ![](docs/924c5d89cc5badfce0f16963e649b6db.webp) 6 | 7 | ## 功能特点 8 | 9 | - 实时摄像头捕获拼图碎片 10 | - 使用 SIFT 算法进行特征匹配 11 | - 自动计算拼图碎片的旋转角度，别管对不对了 12 | - 显示处理过程 13 | 14 | ## 怎样使用 15 | 16 | 预先准备： 17 | 18 | - 拼图的原图 19 | - 摄像头 20 | - 一个和拼图有明显区分的背景，最好是纯色的 21 | - 最好有一个和完成品比例一致的印刷版参考图 22 | 23 | ![](docs/12caad0293628ecba879cd580924a107.webp) 24 | 25 | 这只是个 MVP，你可能需要掌握一点点 Python 知识。 26 | 27 | - 在 `src.main.main` 中修改原图 `base_img` 的路径 28 | - 如果你有多个摄像头，在 `src.main.main` 中修改摄像头的索引 `camera_index` 29 | - 启动 `main.py` 30 | 31 | 主窗口分为四个区域： 32 | 33 | - 左侧：显示原图并使用紫色圆点和绿色框标记匹配区域 34 | - 右上：摄像头实时捕获的画面 35 | - 右中：带掩膜的拼图片 36 | - 右下：匹配成功时显示正确旋转后的拼图片 37 | 38 | 调试： 39 | 40 | - 如果拼图片的掩膜计算效果不佳，调整 `src.camera.create_mask` 的几个参数 41 | - 手动调整摄像头的焦距、感光度、快门速度等参数能够获得更稳定的结果 42 | - 如果你的拼图缺乏特征点（就像我这个的右半边一样），建议使用基于边缘匹配的方案，如 [Kawaboongawa / Zolver](https://github.com/Kawaboongawa/Zolver) 43 | 44 | ## 故事 45 | 46 | 我购入的这款 500 片拼图名为《色达雪景》，原图来自米拍摄影社区的摄影师 Rarobin。 47 | 48 | 色达县是中国四川省甘孜藏族自治州辖县，位于甘孜州东北部，面积 9338.98 平方公里。常住人口 64681 人，「色达」一词意为「金马」。 49 | -------------------------------------------------------------------------------- /base.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ddrpa/jigsight/ec854fb4f180bec4d529f53eeebeeff02dc67817/base.jpg -------------------------------------------------------------------------------- /docs/12caad0293628ecba879cd580924a107.webp: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ddrpa/jigsight/ec854fb4f180bec4d529f53eeebeeff02dc67817/docs/12caad0293628ecba879cd580924a107.webp -------------------------------------------------------------------------------- /docs/924c5d89cc5badfce0f16963e649b6db.webp: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ddrpa/jigsight/ec854fb4f180bec4d529f53eeebeeff02dc67817/docs/924c5d89cc5badfce0f16963e649b6db.webp -------------------------------------------------------------------------------- /src/camera.py: -------------------------------------------------------------------------------- 1 | import cv2 2 | import time 3 | import numpy as np 4 | 5 | 6 | def create_mask(image, blur_size=15, threshold_value=8, morph_size=15): 7 | """ 8 | 为拼图块创建掩膜，排除边缘区域 9 | Args: 10 | image: 输入图像 11 | blur_size: 高斯模糊核大小 12 | threshold_value: 阈值化参数 13 | morph_size: 形态学操作核大小 14 | Returns: 15 | 内部区域掩膜 16 | """ 17 | gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) 18 | blurred = cv2.GaussianBlur(gray, (blur_size, blur_size), 0) 19 | edges = cv2.Canny(blurred, threshold_value, threshold_value * 3) 20 | kernel = np.ones((3, 3), np.uint8) 21 | dilated_edges = cv2.dilate(edges, kernel, iterations=2) 22 | contours, _ = cv2.findContours(dilated_edges, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) 23 | mask = np.zeros_like(gray) 24 | 25 | if contours: 26 | # 找到最大轮廓（假设是拼图块的边界） 27 | max_contour = max(contours, key=cv2.contourArea) 28 | # 填充轮廓内部 29 | cv2.drawContours(mask, [max_contour], 0, 255, -1) 30 | # 腐蚀掩膜，去除边缘区域 31 | morph_kernel = np.ones((morph_size, morph_size), np.uint8) 32 | mask = cv2.erode(mask, morph_kernel, iterations=1) 33 | return mask 34 | 35 | 36 | def open_camera(camera_index, crop_ratio, callback): 37 | cv2.destroyAllWindows() 38 | time.sleep(0.2) 39 | cap = cv2.VideoCapture(camera_index) 40 | if not cap.isOpened(): 41 | print(f"ERROR: camera {camera_index} can not open") 42 | return 43 | width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH)) 44 | height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT)) 45 | crop_width = int(width * crop_ratio) 46 | crop_height = int(height * crop_ratio) 47 | start_x = (width - crop_width) // 2 48 | start_y = (height - crop_height) // 2 49 | end_x = start_x + crop_width 50 | end_y = start_y + crop_height 51 | 52 | print(f"camera {camera_index} on") 53 | print(f"crop ratio: {int(crop_ratio * 100)}%") 54 | print("press ESC to exit") 55 | 56 | try: 57 | while True: 58 | ret, frame = cap.read() 59 | if not ret: 60 | print("ERROR: Unable to capture image") 61 | break 62 | center_area = frame[start_y:end_y, start_x:end_x].copy() 63 | mask = create_mask(center_area) 64 | if callback: 65 | callback(center_area, mask) 66 | key = cv2.waitKey(1) 67 | if key == 27: # ESC 68 | print("exit") 69 | break 70 | finally: 71 | cap.release() 72 | cv2.destroyAllWindows() 73 | time.sleep(0.2) 74 | -------------------------------------------------------------------------------- /src/detector/sift.py: -------------------------------------------------------------------------------- 1 | import cv2 2 | import numpy as np 3 | 4 | 5 | def preprocess(img): 6 | gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) 7 | blurred = cv2.GaussianBlur(gray, (5, 5), 0) 8 | return blurred 9 | 10 | 11 | def match_with_sift(base_image, gray_base, piece, mask): 12 | sift = cv2.SIFT_create() 13 | gray_piece = preprocess(piece) 14 | 15 | kp1, des1 = sift.detectAndCompute(gray_piece, mask) 16 | kp2, des2 = sift.detectAndCompute(gray_base, None) 17 | 18 | if kp1 is None or len(kp1) < 10: 19 | print("特征点太少") 20 | return base_image, None 21 | 22 | bf = cv2.BFMatcher() 23 | matches = bf.knnMatch(des1, des2, k=2) 24 | 25 | good = [] 26 | for m, n in matches: 27 | if m.distance < 0.75 * n.distance: 28 | good.append(m) 29 | 30 | print(f"匹配点数量: {len(good)}") 31 | if len(good) <= 4: 32 | print("匹配点太少") 33 | return base_image, None 34 | 35 | src_pts = np.float32([kp1[m.queryIdx].pt for m in good]).reshape(-1, 1, 2) 36 | dst_pts = np.float32([kp2[m.trainIdx].pt for m in good]).reshape(-1, 1, 2) 37 | 38 | M, mask = cv2.findHomography(src_pts, dst_pts, cv2.RANSAC, 5.0) 39 | 40 | if M is None: 41 | return base_image, None 42 | 43 | h, w = gray_piece.shape[:2] 44 | pts = np.float32([[0, 0], [0, h], [w, h], [w, 0]]).reshape(-1, 1, 2) 45 | dst = cv2.perspectiveTransform(pts, M) 46 | # 绘制匹配区域 47 | matched = base_image.copy() 48 | cv2.polylines(matched, [np.int32(dst)], True, (0, 255, 0), 3) 49 | # 在匹配图上展示使用的关键点 50 | for i, m in enumerate(good): 51 | # 获取原图中的关键点坐标 52 | x2, y2 = kp2[m.trainIdx].pt 53 | cv2.circle(matched, (int(x2), int(y2)), 5, (255, 0, 255), -1) 54 | 55 | angle = -np.arctan2(M[0, 1], M[0, 0]) * 180 / np.pi 56 | return matched, angle 57 | -------------------------------------------------------------------------------- /src/main.py: -------------------------------------------------------------------------------- 1 | import cv2 2 | import numpy as np 3 | 4 | from camera import open_camera 5 | from detector.sift import match_with_sift 6 | 7 | global base_image, gray_base, masked_preview 8 | global last_processing_time 9 | global last_result 10 | 11 | 12 | def rotate_image(image, angle): 13 | height, width = image.shape[:2] 14 | center = (width // 2, height // 2) 15 | 16 | rotation_matrix = cv2.getRotationMatrix2D(center, angle, 1.0) 17 | rotated = cv2.warpAffine(image, rotation_matrix, (width, height), 18 | flags=cv2.INTER_LINEAR, borderMode=cv2.BORDER_CONSTANT, 19 | borderValue=(255, 255, 255)) 20 | return rotated 21 | 22 | 23 | def display(piece, mask, matched_result, angle): 24 | h_match, w_match = matched_result.shape[:2] 25 | left_ratio = 0.7 26 | total_width = int(w_match / left_ratio) 27 | left_width = int(total_width * left_ratio) 28 | right_width = total_width - left_width 29 | 30 | panel_height = h_match // 3 31 | total_height = h_match 32 | 33 | result = np.ones((total_height, total_width, 3), dtype=np.uint8) * 255 34 | 35 | left_height = total_height 36 | left_img = cv2.resize(matched_result, (left_width, left_height)) 37 | result[0:left_height, 0:left_width] = left_img 38 | 39 | right_x = left_width 40 | piece_resized = cv2.resize(piece, (right_width, panel_height)) 41 | result[0:panel_height, right_x:total_width] = piece_resized 42 | 43 | # 摄像头预览 44 | margin_ratio = 0.1 # 边距比例 45 | margin_h = int(panel_height * margin_ratio) 46 | margin_w = int(right_width * margin_ratio) 47 | cv2.rectangle( 48 | result, 49 | (right_x + margin_w, margin_h), 50 | (total_width - margin_w, panel_height - margin_h), 51 | (0, 255, 0), 2 52 | ) 53 | 54 | # 掩膜处理后图像 55 | masked_piece = create_masked_piece(mask, piece) 56 | masked_resized = cv2.resize(masked_piece, (right_width, panel_height)) 57 | result[panel_height:panel_height * 2, right_x:total_width] = masked_resized 58 | 59 | # 匹配成功时显示旋转图像 60 | if angle is not None: 61 | rotated_piece = rotate_image(piece, angle) 62 | rotated_resized = cv2.resize(rotated_piece, (right_width, panel_height)) 63 | result[panel_height * 2:total_height, right_x:total_width] = rotated_resized 64 | angle_text = f"rotated: {angle:.1f}°" 65 | cv2.putText( 66 | result, 67 | angle_text, 68 | (right_x + 10, panel_height * 2 + 30), 69 | cv2.FONT_HERSHEY_SIMPLEX, 70 | 0.6, (0, 0, 0), 1 71 | ) 72 | else: 73 | # 匹配失败时右下区域保持空白 74 | pass 75 | return result 76 | 77 | 78 | def callback_process_frame(piece, mask): 79 | matched_result, angle = match_with_sift(base_image, gray_base, piece, mask) 80 | result_display = display(piece, mask, matched_result, angle) 81 | cv2.imshow("jigsaw", result_display) 82 | 83 | 84 | def create_masked_piece(mask, piece): 85 | # 创建掩膜效果预览 86 | mask_3channel = cv2.merge([mask, mask, mask]) 87 | mask_3channel = mask_3channel.astype(np.float32) / 255 88 | darkened = (piece * 0.3).astype(np.uint8) 89 | masked_area = (piece * mask_3channel).astype(np.uint8) 90 | # 使用掩膜合并 91 | masked_piece = darkened.copy() 92 | masked_piece = np.where(mask_3channel > 0, masked_area, masked_piece) 93 | # 添加掩膜边界线 94 | mask_outline = cv2.dilate(mask, np.ones((3, 3), np.uint8)) - mask 95 | mask_outline_idx = mask_outline > 0 96 | if np.any(mask_outline_idx): 97 | masked_piece[mask_outline_idx] = [0, 0, 255] 98 | return masked_piece 99 | 100 | 101 | def main(): 102 | # 初始化全局变量 103 | global base_image, gray_base 104 | camera_index = 0 105 | crop_ratio = 0.4 106 | base_image = cv2.imread("../base.jpg") 107 | if base_image is None: 108 | print("错误：无法加载原始拼图图像") 109 | return 110 | # 计算原图的灰度图像 111 | gray_base = cv2.cvtColor(base_image, cv2.COLOR_BGR2GRAY) 112 | 113 | cv2.namedWindow("jigsaw", cv2.WINDOW_NORMAL) 114 | open_camera(camera_index, crop_ratio, callback_process_frame) 115 | 116 | 117 | if __name__ == "__main__": 118 | main() 119 | --------------------------------------------------------------------------------