initial commit

alvonCV/FaceDetectionModule.py

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+import cv2
+import time
+import mediapipe as mp
+
+
+class FaceDetector:
+    def __init__(self, minDetectionConf=0.5):
+        self.minDetectionConf = minDetectionConf
+        self.mpFaceDetection = mp.solutions.face_detection
+        self.mpDraw = mp.solutions.drawing_utils
+        self.faceDetection = self.mpFaceDetection.FaceDetection(min_detection_confidence=self.minDetectionConf)
+
+    def findFaces(self, img, draw=False):
+        imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+        self.results = self.faceDetection.process(imgRGB)
+        bboxs = []
+        if self.results.detections:
+            for id, detection in enumerate(self.results.detections):
+                bboxC = detection.location_data.relative_bounding_box
+                ih, iw, ic = img.shape
+                bbox = int(bboxC.xmin * iw), int(bboxC.ymin * ih), \
+                       int(bboxC.width * iw), int(bboxC.height * ih)
+                bboxs.append([id, bbox, detection.score])
+
+                right_eye = (detection.location_data.relative_keypoints[0].x * iw, detection.location_data.relative_keypoints[0].y*ih)
+                if draw:
+                    self.fancyBBoxDraw(img, bbox)
+                    cv2.circle(img, (int(right_eye[0]), int(right_eye[1])), 1, (0, 0, 255), 1)
+                    cv2.putText(img, f'Score: {int(detection.score[0] * 100)}', (bbox[0], bbox[1] - 20),
+                                cv2.FONT_HERSHEY_PLAIN, 2, (255, 0, 255), 2)
+
+        return img, bboxs
+
+    def fancyBBoxDraw(self, img, bbox, l=20, t=6):
+        x, y, w, h = bbox
+        x1, y1 = x + w, y + h
+
+        cv2.rectangle(img, bbox, (255, 0, 255), 2)
+
+        # top left x,y
+        cv2.line(img, (x, y), (x + l, y), (255, 0, 255), t)
+        cv2.line(img, (x, y), (x, y + l), (255, 0, 255), t)
+
+        # top right x1,y
+        cv2.line(img, (x1, y), (x1 - l, y), (255, 0, 255), t)
+        cv2.line(img, (x1, y), (x1, y + l), (255, 0, 255), t)
+
+        # bottom left x,y1
+        cv2.line(img, (x, y1), (x + l, y1), (255, 0, 255), t)
+        cv2.line(img, (x, y1), (x, y1 - l), (255, 0, 255), t)
+
+        # bottom right x1,y1
+        cv2.line(img, (x1, y1), (x1 - l, y1), (255, 0, 255), t)
+        cv2.line(img, (x1, y1), (x1, y1 - l), (255, 0, 255), t)
+
+        return img
+
+
+def main():
+    cap = cv2.VideoCapture(0)
+    pTime = 0
+    faceDetectorObj = FaceDetector()
+
+    while True:
+        success, img = cap.read()
+        img, bboxs = faceDetectorObj.findFaces(img, draw=True)
+        cTime = time.time()
+        fps = 1 / (cTime - pTime)
+        pTime = cTime
+        cv2.putText(img, f'FPS: {int(fps)}', (20, 70), cv2.FONT_HERSHEY_PLAIN, 3, (0, 255, 0), 2)
+        cv2.imshow("Image", img)
+        cv2.waitKey(1)
+
+
+if __name__ == "__main__":
+    main()

alvonCV/FaceMeshModule.py

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+import cv2
+import mediapipe as mp
+import time
+
+
+class FaceMeshDetector:
+    def __init__(self, staticMode=False, maxFaces=5, minDetectionConf=0.5, minTrackConf=0.5):
+        self.staticMode = staticMode
+        self.maxFaces = maxFaces
+        self.minDetectionConf = minDetectionConf
+        self.minTrackConf = minTrackConf
+
+        self.mpDraw = mp.solutions.drawing_utils
+        self.mpFaceMesh = mp.solutions.face_mesh
+        self.facemesh = self.mpFaceMesh.FaceMesh(self.staticMode, self.maxFaces,
+                                                 self.minDetectionConf, self.minTrackConf)
+        self.drawSpec = self.mpDraw.DrawingSpec(thickness=1, circle_radius=1)
+
+    def findFaceMesh(self, img, draw=True):
+        self.imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+        self.results = self.facemesh.process(self.imgRGB)
+        faces = []
+        if self.results.multi_face_landmarks:
+            for faceLms in self.results.multi_face_landmarks:
+                if draw:
+                    self.mpDraw.draw_landmarks(img, faceLms, self.mpFaceMesh.FACE_CONNECTIONS, self.drawSpec, self.drawSpec)
+
+                face = []
+                for id, lm in enumerate(faceLms.landmark):
+                    ih, iw, ic = img.shape
+                    x, y = int(lm.x*iw), int(lm.y*ih)
+                    face.append([x, y])
+                faces.append(face)
+
+        return img
+
+
+def main():
+    cap = cv2.VideoCapture(0)
+    pTime = 0
+    detector = FaceMeshDetector()
+    while True:
+        success, img = cap.read()
+
+        img, faces = detector.findFaceMesh(img)
+        if len(faces):
+            print(len(faces))
+
+        cTime = time.time()
+        fps = 1 / (cTime - pTime)
+        pTime = cTime
+        cv2.putText(img, f'FPS: {int(fps)}', (20, 70), cv2.FONT_HERSHEY_PLAIN, 2, (0, 255, 0), 2)
+        cv2.imshow('Image', img)
+        cv2.waitKey(1)
+
+
+if __name__ == "__main__":
+    main()

alvonCV/__init__.py

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+from alvonCV.FaceMeshModule import FaceMeshDetector
+from alvonCV.FaceDetectionModule import FaceDetector

setup.py

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+from distutils.core import setup
+
+setup(
+    name='alvonCV',  # How you named your package folder (MyLib)
+    packages=['alvonCV'],  # Chose the same as "name"
+    version='0.1',  # Start with a small number and increase it with every change you make
+    license='MIT',  # Chose a license from here: https://help.github.com/articles/licensing-a-repository
+    description='Computer Vision Helper Package',  # Give a short description about your library
+    author='Deepak Singh',  # Type in your name
+    author_email='deepaksinghgs30@gmail.com',  # Type in your E-Mail
+    url='https://github.com/alvon-X/alvonCV',  # Provide either the link to your github or to your website
+    download_url='https://github.com/user/reponame/archive/v_01.tar.gz',  # I explain this later on
+    keywords=['Computer Vision', 'Face Mesh', 'Face Detection', 'alvon'],  # Keywords that define your package best
+    install_requires=[  # I get to this in a second
+        'opencv-python',
+        'mediapipe',
+    ],
+    classifiers=[
+        'Development Status :: 3 - Alpha',
+        # Chose either "3 - Alpha", "4 - Beta" or "5 - Production/Stable" as the current state of your package
+        'Intended Audience :: Developers',  # Define that your audience are developers
+        'Topic :: Software Development :: Build Tools',
+        'License :: OSI Approved :: MIT License',  # Again, pick a license
+        'Programming Language :: Python :: 3.6',  # Specify which pyhton versions that you want to support
+        'Programming Language :: Python :: 3.7',
+        'Programming Language :: Python :: 3.8',
+    ],
+)