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Open Source Computer Vision Library
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67 lines
1.9 KiB
67 lines
1.9 KiB
#!/usr/bin/env python |
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''' |
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VideoCapture sample showcasing some features of the Video4Linux2 backend |
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Sample shows how VideoCapture class can be used to control parameters |
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of a webcam such as focus or framerate. |
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Also the sample provides an example how to access raw images delivered |
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by the hardware to get a grayscale image in a very efficient fashion. |
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Keys: |
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ESC - exit |
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g - toggle optimized grayscale conversion |
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''' |
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# Python 2/3 compatibility |
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from __future__ import print_function |
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import cv2 |
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def decode_fourcc(v): |
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v = int(v) |
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return "".join([chr((v >> 8 * i) & 0xFF) for i in range(4)]) |
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font = cv2.FONT_HERSHEY_SIMPLEX |
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color = (0, 255, 0) |
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cap = cv2.VideoCapture(0) |
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cap.set(cv2.CAP_PROP_AUTOFOCUS, False) # Known bug: https://github.com/opencv/opencv/pull/5474 |
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cv2.namedWindow("Video") |
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convert_rgb = True |
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fps = int(cap.get(cv2.CAP_PROP_FPS)) |
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focus = int(min(cap.get(cv2.CAP_PROP_FOCUS) * 100, 2**31-1)) # ceil focus to C_LONG as Python3 int can go to +inf |
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cv2.createTrackbar("FPS", "Video", fps, 30, lambda v: cap.set(cv2.CAP_PROP_FPS, v)) |
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cv2.createTrackbar("Focus", "Video", focus, 100, lambda v: cap.set(cv2.CAP_PROP_FOCUS, v / 100)) |
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while True: |
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status, img = cap.read() |
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fourcc = decode_fourcc(cap.get(cv2.CAP_PROP_FOURCC)) |
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fps = cap.get(cv2.CAP_PROP_FPS) |
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if not bool(cap.get(cv2.CAP_PROP_CONVERT_RGB)): |
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if fourcc == "MJPG": |
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img = cv2.imdecode(img, cv2.IMREAD_GRAYSCALE) |
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elif fourcc == "YUYV": |
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img = cv2.cvtColor(img, cv2.COLOR_YUV2GRAY_YUYV) |
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else: |
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print("unsupported format") |
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break |
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cv2.putText(img, "Mode: {}".format(fourcc), (15, 40), font, 1.0, color) |
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cv2.putText(img, "FPS: {}".format(fps), (15, 80), font, 1.0, color) |
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cv2.imshow("Video", img) |
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k = 0xFF & cv2.waitKey(1) |
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if k == 27: |
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break |
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elif k == ord("g"): |
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convert_rgb = not convert_rgb |
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cap.set(cv2.CAP_PROP_CONVERT_RGB, convert_rgb)
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