Intensity -> Radial mapping for SWIM waveform generation from single LED SWMs
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
#!/usr/bin/env python | |
from PIL import Image, ImageFilter, ImageOps | |
import numpy as np | |
import math | |
import scipy.sparse | |
import cv2 | |
import pdb | |
import sys | |
import pyvirtualcam | |
V = cv2.VideoCapture(0) | |
DOWNSCALE = 2 | |
H, W = int(V.get(cv2.CAP_PROP_FRAME_HEIGHT) / DOWNSCALE), int(V.get(cv2.CAP_PROP_FRAME_WIDTH) / DOWNSCALE) | |
with pyvirtualcam.Camera(width=W, height=H, fps=20, fmt=pyvirtualcam.PixelFormat.BGR) as Vout: | |
codec = cv2.VideoWriter_fourcc(*'MP4V') | |
SKIP = 4 | |
YX = np.mgrid[0:H,0:W] | |
C = (0, np.zeros((2,))) # weight, coord | |
ALPHA = 0.95 # exponential factor | |
SCALE = 1 | |
frame = 0 | |
frame_buf = np.zeros((H, W, 3, 2)) | |
while V.isOpened(): | |
frame += 1 | |
valid, im_raw = V.read() | |
if not valid: | |
break | |
# if frame % SKIP == 0: | |
# continue | |
im_raw = im_raw[(DOWNSCALE-1)::DOWNSCALE,(DOWNSCALE-1)::DOWNSCALE] | |
im = im_raw[:,:,0] # blue only | |
Etot = max(1, im.sum()) # max(1, im_thresh.sum()) | |
alpha_ = np.arctan(C[0] / Etot * math.tan(ALPHA * math.pi / 2)) / (math.pi / 2) | |
C = ( | |
alpha_ * C[0] + (1 - alpha_) * Etot, | |
alpha_ * C[1] + (1 - alpha_) * np.sum(im * YX, axis=(1,2)) / Etot | |
) | |
c_ = C[1][:,np.newaxis] | |
BLUR_SIZE = 5 | |
imflat = im.flatten().astype(np.uint32) # * (BLUR_SIZE ** 2) | |
xy_ = np.maximum((c_ + (YX.reshape((2,-1)) - c_) * (1 + imflat / 256) * SCALE).astype(np.int32), 0) | |
gray_raw = scipy.sparse.coo_matrix((imflat, xy_)).toarray() # np.sqrt(imflat) * (255 / np.sqrt(255)) | |
frame_out = np.zeros((H, W, 3)) | |
frame_out[:,:,0:2] = gray_raw[:H, :W, np.newaxis] # np.tile( # duplicates are summed together | |
# Image.fromarray(frame_out).show() | |
# sys.stdout.write('\r%d' % frame) | |
frame_buf[:,:,:,frame%(frame_buf.shape[3])] = frame_out | |
frame_out_b = np.minimum(255, frame_buf.sum(axis=3)).astype(np.uint8) | |
frame_comp = cv2.add(cv2.boxFilter(frame_out_b, -1, (3,3), normalize=False), im_raw) | |
cv2.circle(frame_comp, C[1][::-1].astype(np.uint32), 3, (0, 0, 255), -1) | |
Vout.send(frame_comp) | |
sys.stdout.write('\r%d' % frame) | |
V.release() | |
cv2.destroyAllWindows() |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment