first commit

.gitignore

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+venv
+.vscode
+__pycache__
+.DS_Store

LICENSE

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+MIT License
+
+Copyright (c) 2020 Cyril Diagne
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

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+# ScreenPoint
+
+Finds the (x,y) coordinates of the centroid of an image (eg: a mobile phone camera image) pointing at another image (eg: a computer screen) using [OpenCV SIFT](https://docs.opencv.org/2.4/modules/nonfree/doc/feature_detection.html).
+
+![debug view](example/match_debug.png)
+
+## Installation
+
+```bash
+pip install screenpoint
+```
+
+## Usage
+
+```python
+import screenpoint
+import cv2
+
+# Load input images.
+screen = cv2.imread('screen.png', 0)
+view = cv2.imread('view.jpg', 0)
+
+# Project view centroid to screen space.
+# x and y are the coordinate of the `view` centroid in `screen` space.
+x, y = screenpoint.project(view, screen)
+```
+
+See [example.py](example.py) for more information.

example.py

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+import screenpoint
+import cv2
+
+# Load input images.
+screen = cv2.imread('example/screen.png', 0)
+view = cv2.imread('example/view.jpg', 0)
+
+# Project centroid.
+x, y, img_debug = screenpoint.project(view, screen, True)
+
+# Write debug image.
+cv2.imwrite('example/match_debug.png', img_debug)

requirements.txt

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+opencv-contrib-python==3.4.2.17

screenpoint/__init__.py

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+from . import screenpoint
+
+project = screenpoint.project

screenpoint/screenpoint.py

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+import numpy as np
+import cv2
+import logging
+
+MIN_MATCH_COUNT = 6
+FLANN_INDEX_KDTREE = 0
+
+sift = cv2.xfeatures2d.SIFT_create()
+
+
+def project(view, screen, debug):
+    kp_screen, des_screen = sift.detectAndCompute(screen, None)
+    kp_view, des_view = sift.detectAndCompute(view, None)
+
+    index_params = dict(algorithm=FLANN_INDEX_KDTREE, trees=5)
+    search_params = dict(checks=50)
+    flann = cv2.FlannBasedMatcher(index_params, search_params)
+    matches = flann.knnMatch(des_screen, des_view, k=2)
+
+    # Store all good matches as per Lowe's ration test
+    good = []
+    for m, n in matches:
+        if m.distance < 0.7 * n.distance:
+            good.append(m)
+
+    if len(good) < MIN_MATCH_COUNT:
+        logging.debug("ScreenPoint: Not enough matches.")
+        return -1, -1
+
+    screen_pts = np.float32([kp_screen[m.queryIdx].pt
+                             for m in good]).reshape(-1, 1, 2)
+    view_pts = np.float32([kp_view[m.trainIdx].pt
+                           for m in good]).reshape(-1, 1, 2)
+
+    h, w = view.shape
+    M, mask = cv2.findHomography(view_pts, screen_pts, cv2.RANSAC, 5.0)
+
+    pts = np.float32([[(w - 1) * 0.5, (h - 1) * 0.5]]).reshape(-1, 1, 2)
+    dst = cv2.perspectiveTransform(pts, M)
+    x, y = np.int32(dst[0][0])
+
+    if debug:
+        img_debug = draw_debug_(x, y, view, screen, M, mask, kp_screen,
+                                kp_view, good)
+        return x, y, img_debug
+    else:
+        return x, y
+
+
+def draw_debug_(x, y, view, screen, M, mask, kp_screen, kp_view, good):
+
+    matchesMask = mask.ravel().tolist()
+    draw_params = dict(
+        matchColor=(0, 255, 0),  # draw matches in green color
+        singlePointColor=None,
+        matchesMask=matchesMask,  # draw only inliers
+        flags=2)
+    img_debug = cv2.drawMatches(screen, kp_screen, view, kp_view, good, None,
+                                **draw_params)
+
+    # Get view centroid coordinates in img_debug space.
+    cx = int(view.shape[1] * 0.5 + screen.shape[1])
+    cy = int(view.shape[0] * 0.5)
+    # Draw view outline.
+    cv2.rectangle(img_debug, (screen.shape[1], 0),
+                  (img_debug.shape[1] - 2, img_debug.shape[0] - 2),
+                  (0, 0, 255), 2)
+    # draw connecting line.
+    cv2.polylines(img_debug, [np.int32([(x, y), (cx, cy)])], True,
+                  (100, 100, 255), 1, cv2.LINE_AA)
+    # Draw query/match markers.
+    cv2.drawMarker(img_debug, (cx, cy), (0, 0, 255), cv2.MARKER_CROSS, 30, 2)
+    cv2.circle(img_debug, (x, y), 10, (0, 0, 255), -1)
+
+    return img_debug

setup.cfg

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+[metadata]
+description-file = README.md

setup.py

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+from distutils.core import setup
+
+setup(
+    name='screenpoint',
+    packages=['screenpoint'],
+    version='0.1.0',
+    license='MIT',
+    description='Project an image centroid to another image using OpenCV',
+    author='Cyril Diagne',
+    author_email='diagne.cyril@gmail.com',
+    url='https://github.com/cyrildiagne/screenpoint',
+    download_url=
+    'https://github.com/cyrildiagne/screenpoint/archive/v0.1.0.tar.gz',
+    keywords=['opencv', 'sift', 'projection'],
+    install_requires=[
+        'opencv-contrib-python==3.4.2.17',
+    ],
+    classifiers=[
+        'Development Status :: 3 - Alpha',
+        'Intended Audience :: Developers',
+        'Topic :: Software Development :: Build Tools',
+        'License :: OSI Approved :: MIT License',
+        'Programming Language :: Python :: 3',
+        'Programming Language :: Python :: 3.4',
+        'Programming Language :: Python :: 3.5',
+        'Programming Language :: Python :: 3.6',
+    ],
+)