@@ -1,16 +1,13 @@
# SPDX-License-Identifier: GPL-2.0-or-later
# Copyright (C) 2022, Tomi Valkeinen <tomi.valkeinen@ideasonboard.com>
-#
-# Debayering code from PiCamera documentation
+from helpers import mfb_to_rgb
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 libcamera as libcam
import libcamera.utils
-import numpy as np
import sys
@@ -21,157 +18,6 @@ def rgb_to_pix(rgb):
return pix
-def demosaic(data, r0, g0, g1, b0):
- # Separate the components from the Bayer data to RGB planes
-
- 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
-
- # 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 by a byte 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 = 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.width
- h = size.height
-
- if fmt == libcam.formats.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 == libcam.formats.RGB888:
- rgb = data.reshape((h, w, 3))
- rgb[:, :, [0, 1, 2]] = rgb[:, :, [2, 1, 0]]
-
- elif fmt == libcam.formats.BGR888:
- rgb = data.reshape((h, w, 3))
-
- elif fmt in [libcam.formats.ARGB8888, libcam.formats.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 str(fmt).startswith('S'):
- fmt = str(fmt)
- 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 = demosaic(data, r0, g0, g1, b0)
- rgb = (rgb >> 8).astype(np.uint8)
-
- else:
- rgb = None
-
- return rgb
-
-
-# A naive format conversion to 24-bit RGB
-def mfb_to_rgb(mfb, cfg):
- data = np.array(mfb.planes[0], dtype=np.uint8)
- rgb = to_rgb(cfg.pixel_format, cfg.size, data)
- return rgb
-
-
class QtRenderer:
def __init__(self, state):
self.state = state
similarity index 55%
copy from src/py/cam/cam_qt.py
copy to src/py/cam/helpers.py
@@ -3,22 +3,10 @@
#
# 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 libcamera as libcam
import libcamera.utils
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 demosaic(data, r0, g0, g1, b0):
@@ -166,147 +154,7 @@ def to_rgb(fmt, size, data):
# A naive format conversion to 24-bit RGB
-def mfb_to_rgb(mfb, cfg):
+def mfb_to_rgb(mfb: libcamera.utils.MappedFrameBuffer, cfg: libcam.StreamConfiguration):
data = np.array(mfb.planes[0], dtype=np.uint8)
rgb = to_rgb(cfg.pixel_format, cfg.size, data)
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:
- for stream in ctx.streams:
- window = MainWindow(ctx, stream)
- window.show()
- windows.append(window)
-
- self.windows = windows
-
- def run(self):
- camnotif = QtCore.QSocketNotifier(self.cm.event_fd, QtCore.QSocketNotifier.Read)
- camnotif.activated.connect(lambda _: self.readcam())
-
- keynotif = QtCore.QSocketNotifier(sys.stdin.fileno(), QtCore.QSocketNotifier.Read)
- keynotif.activated.connect(lambda _: self.readkey())
-
- print('Capturing...')
-
- self.app.exec()
-
- print('Exiting...')
-
- def readcam(self):
- running = self.state.event_handler()
-
- 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_processed(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 cid, cv in camera.properties.items():
- lab = QtWidgets.QLabel()
- lab.setText('{} = {}'.format(cid, cv))
- groupLayout.addWidget(lab)
-
- group = QtWidgets.QGroupBox('Controls')
- groupLayout = QtWidgets.QVBoxLayout()
- group.setLayout(groupLayout)
- controlsLayout.addWidget(group)
-
- for cid, cinfo in camera.controls.items():
- lab = QtWidgets.QLabel()
- lab.setText('{} = {}/{}/{}'
- .format(cid, cinfo.min, cinfo.max, cinfo.default))
- groupLayout.addWidget(lab)
-
- controlsLayout.addStretch()
-
- def buf_to_qpixmap(self, stream, fb):
- with libcamera.utils.MappedFrameBuffer(fb) as mfb:
- cfg = stream.configuration
-
- if cfg.pixel_format == libcam.formats.MJPEG:
- img = Image.open(BytesIO(mfb.planes[0]))
- qim = ImageQt(img).copy()
- pix = QtGui.QPixmap.fromImage(qim)
- else:
- rgb = mfb_to_rgb(mfb, cfg)
- 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))