1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
|
# SPDX-License-Identifier: GPL-2.0-or-later
# Copyright (C) 2022, Tomi Valkeinen <tomi.valkeinen@ideasonboard.com>
#
# Debayering code from PiCamera documentation
from io import BytesIO
from numpy.lib.stride_tricks import as_strided
from PIL import Image
from PIL.ImageQt import ImageQt
from PyQt5 import QtCore, QtGui, QtWidgets
import numpy as np
import sys
def rgb_to_pix(rgb):
img = Image.frombuffer('RGB', (rgb.shape[1], rgb.shape[0]), rgb)
qim = ImageQt(img).copy()
pix = QtGui.QPixmap.fromImage(qim)
return pix
def separate_components(data, r0, g0, g1, b0):
# Now to split the data up into its red, green, and blue components. The
# Bayer pattern of the OV5647 sensor is BGGR. In other words the first
# row contains alternating green/blue elements, the second row contains
# alternating red/green elements, and so on as illustrated below:
#
# GBGBGBGBGBGBGB
# RGRGRGRGRGRGRG
# GBGBGBGBGBGBGB
# RGRGRGRGRGRGRG
#
# Please note that if you use vflip or hflip to change the orientation
# of the capture, you must flip the Bayer pattern accordingly
rgb = np.zeros(data.shape + (3,), dtype=data.dtype)
rgb[r0[1]::2, r0[0]::2, 0] = data[r0[1]::2, r0[0]::2] # Red
rgb[g0[1]::2, g0[0]::2, 1] = data[g0[1]::2, g0[0]::2] # Green
rgb[g1[1]::2, g1[0]::2, 1] = data[g1[1]::2, g1[0]::2] # Green
rgb[b0[1]::2, b0[0]::2, 2] = data[b0[1]::2, b0[0]::2] # Blue
return rgb
def demosaic(rgb, r0, g0, g1, b0):
# At this point we now have the raw Bayer data with the correct values
# and colors but the data still requires de-mosaicing and
# post-processing. If you wish to do this yourself, end the script here!
#
# Below we present a fairly naive de-mosaic method that simply
# calculates the weighted average of a pixel based on the pixels
# surrounding it. The weighting is provided b0[1] a b0[1]te representation of
# the Bayer filter which we construct first:
bayer = np.zeros(rgb.shape, dtype=np.uint8)
bayer[r0[1]::2, r0[0]::2, 0] = 1 # Red
bayer[g0[1]::2, g0[0]::2, 1] = 1 # Green
bayer[g1[1]::2, g1[0]::2, 1] = 1 # Green
bayer[b0[1]::2, b0[0]::2, 2] = 1 # Blue
# Allocate an array to hold our output with the same shape as the input
# data. After this we define the size of window that will be used to
# calculate each weighted average (3x3). Then we pad out the rgb and
# bayer arrays, adding blank pixels at their edges to compensate for the
# size of the window when calculating averages for edge pixels.
output = np.empty(rgb.shape, dtype=rgb.dtype)
window = (3, 3)
borders = (window[0] - 1, window[1] - 1)
border = (borders[0] // 2, borders[1] // 2)
# rgb_pad = np.zeros((
# rgb.shape[0] + borders[0],
# rgb.shape[1] + borders[1],
# rgb.shape[2]), dtype=rgb.dtype)
# rgb_pad[
# border[0]:rgb_pad.shape[0] - border[0],
# border[1]:rgb_pad.shape[1] - border[1],
# :] = rgb
# rgb = rgb_pad
#
# bayer_pad = np.zeros((
# bayer.shape[0] + borders[0],
# bayer.shape[1] + borders[1],
# bayer.shape[2]), dtype=bayer.dtype)
# bayer_pad[
# border[0]:bayer_pad.shape[0] - border[0],
# border[1]:bayer_pad.shape[1] - border[1],
# :] = bayer
# bayer = bayer_pad
# In numpy >=1.7.0 just use np.pad (version in Raspbian is 1.6.2 at the
# time of writing...)
#
rgb = np.pad(rgb, [
(border[0], border[0]),
(border[1], border[1]),
(0, 0),
], 'constant')
bayer = np.pad(bayer, [
(border[0], border[0]),
(border[1], border[1]),
(0, 0),
], 'constant')
# For each plane in the RGB data, we use a nifty numpy trick
# (as_strided) to construct a view over the plane of 3x3 matrices. We do
# the same for the bayer array, then use Einstein summation on each
# (np.sum is simpler, but copies the data so it's slower), and divide
# the results to get our weighted average:
for plane in range(3):
p = rgb[..., plane]
b = bayer[..., plane]
pview = as_strided(p, shape=(
p.shape[0] - borders[0],
p.shape[1] - borders[1]) + window, strides=p.strides * 2)
bview = as_strided(b, shape=(
b.shape[0] - borders[0],
b.shape[1] - borders[1]) + window, strides=b.strides * 2)
psum = np.einsum('ijkl->ij', pview)
bsum = np.einsum('ijkl->ij', bview)
output[..., plane] = psum // bsum
return output
def to_rgb(fmt, size, data):
w = size[0]
h = size[1]
if fmt == 'YUYV':
# YUV422
yuyv = data.reshape((h, w // 2 * 4))
# YUV444
yuv = np.empty((h, w, 3), dtype=np.uint8)
yuv[:, :, 0] = yuyv[:, 0::2] # Y
yuv[:, :, 1] = yuyv[:, 1::4].repeat(2, axis=1) # U
yuv[:, :, 2] = yuyv[:, 3::4].repeat(2, axis=1) # V
m = np.array([
[1.0, 1.0, 1.0],
[-0.000007154783816076815, -0.3441331386566162, 1.7720025777816772],
[1.4019975662231445, -0.7141380310058594, 0.00001542569043522235]
])
rgb = np.dot(yuv, m)
rgb[:, :, 0] -= 179.45477266423404
rgb[:, :, 1] += 135.45870971679688
rgb[:, :, 2] -= 226.8183044444304
rgb = rgb.astype(np.uint8)
elif fmt == 'RGB888':
rgb = data.reshape((h, w, 3))
rgb[:, :, [0, 1, 2]] = rgb[:, :, [2, 1, 0]]
elif fmt == 'BGR888':
rgb = data.reshape((h, w, 3))
elif fmt in ['ARGB8888', 'XRGB8888']:
rgb = data.reshape((h, w, 4))
rgb = np.flip(rgb, axis=2)
# drop alpha component
rgb = np.delete(rgb, np.s_[0::4], axis=2)
elif fmt.startswith('S'):
bayer_pattern = fmt[1:5]
bitspp = int(fmt[5:])
# TODO: shifting leaves the lowest bits 0
if bitspp == 8:
data = data.reshape((h, w))
data = data.astype(np.uint16) << 8
elif bitspp in [10, 12]:
data = data.view(np.uint16)
data = data.reshape((h, w))
data = data << (16 - bitspp)
else:
raise Exception('Bad bitspp:' + str(bitspp))
idx = bayer_pattern.find('R')
assert(idx != -1)
r0 = (idx % 2, idx // 2)
idx = bayer_pattern.find('G')
assert(idx != -1)
g0 = (idx % 2, idx // 2)
idx = bayer_pattern.find('G', idx + 1)
assert(idx != -1)
g1 = (idx % 2, idx // 2)
idx = bayer_pattern.find('B')
assert(idx != -1)
b0 = (idx % 2, idx // 2)
rgb = separate_components(data, r0, g0, g1, b0)
rgb = demosaic(rgb, r0, g0, g1, b0)
rgb = (rgb >> 8).astype(np.uint8)
else:
rgb = None
return rgb
class QtRenderer:
def __init__(self, state):
self.state = state
self.cm = state['cm']
self.contexts = state['contexts']
def setup(self):
self.app = QtWidgets.QApplication([])
windows = []
for ctx in self.contexts:
camera = ctx['camera']
for stream in ctx['streams']:
fmt = stream.configuration.pixel_format
size = stream.configuration.size
window = MainWindow(ctx, stream)
window.setAttribute(QtCore.Qt.WA_ShowWithoutActivating)
window.show()
windows.append(window)
self.windows = windows
def run(self):
camnotif = QtCore.QSocketNotifier(self.cm.efd, QtCore.QSocketNotifier.Read)
camnotif.activated.connect(lambda x: self.readcam())
keynotif = QtCore.QSocketNotifier(sys.stdin.fileno(), QtCore.QSocketNotifier.Read)
keynotif.activated.connect(lambda x: self.readkey())
print('Capturing...')
self.app.exec()
print('Exiting...')
def readcam(self):
running = self.state['event_handler'](self.state)
if not running:
self.app.quit()
def readkey(self):
sys.stdin.readline()
self.app.quit()
def request_handler(self, ctx, req):
buffers = req.buffers
for stream, fb in buffers.items():
wnd = next(wnd for wnd in self.windows if wnd.stream == stream)
wnd.handle_request(stream, fb)
self.state['request_prcessed'](ctx, req)
def cleanup(self):
for w in self.windows:
w.close()
class MainWindow(QtWidgets.QWidget):
def __init__(self, ctx, stream):
super().__init__()
self.ctx = ctx
self.stream = stream
self.label = QtWidgets.QLabel()
windowLayout = QtWidgets.QHBoxLayout()
self.setLayout(windowLayout)
windowLayout.addWidget(self.label)
controlsLayout = QtWidgets.QVBoxLayout()
windowLayout.addLayout(controlsLayout)
windowLayout.addStretch()
group = QtWidgets.QGroupBox('Info')
groupLayout = QtWidgets.QVBoxLayout()
group.setLayout(groupLayout)
controlsLayout.addWidget(group)
lab = QtWidgets.QLabel(ctx['id'])
groupLayout.addWidget(lab)
self.frameLabel = QtWidgets.QLabel()
groupLayout.addWidget(self.frameLabel)
group = QtWidgets.QGroupBox('Properties')
groupLayout = QtWidgets.QVBoxLayout()
group.setLayout(groupLayout)
controlsLayout.addWidget(group)
camera = ctx['camera']
for k, v in camera.properties.items():
lab = QtWidgets.QLabel()
lab.setText(k + ' = ' + str(v))
groupLayout.addWidget(lab)
group = QtWidgets.QGroupBox('Controls')
groupLayout = QtWidgets.QVBoxLayout()
group.setLayout(groupLayout)
controlsLayout.addWidget(group)
for k, (min, max, default) in camera.controls.items():
lab = QtWidgets.QLabel()
lab.setText('{} = {}/{}/{}'.format(k, min, max, default))
groupLayout.addWidget(lab)
controlsLayout.addStretch()
def buf_to_qpixmap(self, stream, fb):
with fb.mmap() as mfb:
cfg = stream.configuration
w, h = cfg.size
pitch = cfg.stride
if cfg.pixel_format == 'MJPEG':
img = Image.open(BytesIO(mfb.planes[0]))
qim = ImageQt(img).copy()
pix = QtGui.QPixmap.fromImage(qim)
else:
data = np.array(mfb.planes[0], dtype=np.uint8)
rgb = to_rgb(cfg.pixel_format, cfg.size, data)
if rgb is None:
raise Exception('Format not supported: ' + cfg.pixel_format)
pix = rgb_to_pix(rgb)
return pix
def handle_request(self, stream, fb):
ctx = self.ctx
pix = self.buf_to_qpixmap(stream, fb)
self.label.setPixmap(pix)
self.frameLabel.setText('Queued: {}\nDone: {}\nFps: {:.2f}'
.format(ctx['reqs-queued'], ctx['reqs-completed'], ctx['fps']))
|