FaceRecogKnn.py

import cv2,time
import pickle
import face_recognition
from face_recognition.face_recognition_cli import image_files_in_folder
def predict(img_path, knn_clf=None, model_path=None, threshold=0.6): # 6 needs 40+ accuracy, 4 needs 60+ accuracy
    if knn_clf is None and model_path is None:
        raise Exception("Must supply knn classifier either thourgh knn_clf or model_path")
    # Load a trained KNN model (if one was passed in)
    if knn_clf is None:
        with open(model_path, 'rb') as f:
            knn_clf = pickle.load(f)
    # Load image file and find face locations
    img = img_path
    face_box = face_recognition.face_locations(img)
    # If no faces are found in the image, return an empty result.
    if len(face_box) == 0:
        return []
    # Find encodings for faces in the test iamge
    faces_encodings = face_recognition.face_encodings(img, known_face_locations=face_box)
    # Use the KNN model to find the best matches for the test face
    closest_distances = knn_clf.kneighbors(faces_encodings, n_neighbors=2)
    matches = [closest_distances[0][i][0] <= threshold for i in range(len(face_box))]
    # Predict classes and remove classifications that aren't within the threshold
    return [(pred, loc) if rec else ("unknown", loc) for pred, loc, rec in zip(knn_clf.predict(faces_encodings),face_box,matches
    )]
webcam = cv2.VideoCapture(0) #  0 to use webcam 
while True:
    # Loop until the camera is working
    rval = False
    while(not rval):
        # Put the image from the webcam into 'frame'
        (rval, frame) = webcam.read()
        if(not rval):
            print("Failed to open webcam. Trying again...")
            
    # Flip the image (optional)
    frame=cv2.flip(frame,1) # 0 = horizontal ,1 = vertical , -1 = both
    frame_copy = cv2.resize(frame, (0, 0), fx=0.25, fy=0.25)
    # Convert the image from BGR color (which OpenCV uses) to RGB color (which face_recognition uses)
    frame_copy=cv2.cvtColor(frame_copy, cv2.COLOR_BGR2RGB)
    predictions = predict(frame_copy, model_path="") # add path here
    font = cv2.FONT_HERSHEY_DUPLEX
    for name, (top, right, bottom, left) in predictions:
        top *= 4 #scale back the frame since it was scaled to 1/4 in size
        right *= 4
        bottom *= 4
        left *= 4
        cv2.rectangle(frame, (left, top), (right, bottom), (0, 255, 255), 2)
        cv2.putText(frame, name, (left-10,top-6), font, 0.8, (255, 255, 255), 1)
        
    cv2.imshow('Video', frame)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break
webcam.release()
cv2.destroyAllWindows()