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jakechen/opencv-python_rekognition.py

Created September 20, 2017 15:38
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  1. jakechen created this gist Sep 20, 2017.
    33 changes: 33 additions & 0 deletions opencv-python_rekognition.py
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    # With help from https://aws.amazon.com/blogs/ai/build-your-own-face-recognition-service-using-amazon-rekognition/

    frame_skip = 100 # analyze every 100 frames to cut down on Rekognition API calls

    import boto3
    import cv2
    from PIL import Image
    import io

    rekog = boto3.client('rekognition')

    vidcap = cv2.VideoCapture('./video_clip.mp4') # Load clip from storage. Can modify this to input from camera.
    cur_frame = 0
    success = True

    while success:

    success, frame = vidcap.read() # get next frame from video

    if cur_frame % frame_skip == 0: # only analyze every n frames
    print('frame: {}'.format(cur_frame))

    pil_img = Image.fromarray(frame) # convert opencv frame (with type()==numpy) into PIL Image
    stream = io.BytesIO()
    pil_img.save(stream, format='JPEG') # convert PIL Image to Bytes
    bin_img = stream.getvalue()

    response = rekog.recognize_celebrities(Image={'Bytes': bin_img}) # call Rekognition
    if response['CelebrityFaces']: # print celebrity name if a celebrity is detected
    for face in response['CelebrityFaces']:
    print('Celebrity is {} with confidence of {}'.format(face['Name'], face['MatchConfidence']))

    cur_frame += 1