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#!/usr/bin/env python3

# SPDX-License-Identifier: BSD-3-Clause
# Copyright (C) 2022, Tomi Valkeinen <tomi.valkeinen@ideasonboard.com>

# A simple capture example extending the simple-capture.py example:
# - Capture frames using events from multiple cameras
# - Listening events from stdin to exit the application
# - Memory mapping the frames and calculating CRC

import binascii
import libcamera as libcam
import libcamera.utils
import selectors
import sys


# A container class for our state per camera
class CameraCaptureContext:
    idx: int
    cam: libcam.Camera
    reqs: list[libcam.Request]
    mfbs: dict[libcam.FrameBuffer, libcamera.utils.MappedFrameBuffer]

    def __init__(self, cam, idx):
        self.idx = idx
        self.cam = cam

        # Acquire the camera for our use

        cam.acquire()

        # Configure the camera

        cam_config = cam.generate_configuration([libcam.StreamRole.Viewfinder])

        stream_config = cam_config.at(0)

        cam.configure(cam_config)

        stream = stream_config.stream

        # Allocate the buffers for capture

        allocator = libcam.FrameBufferAllocator(cam)
        ret = allocator.allocate(stream)
        assert ret > 0

        num_bufs = len(allocator.buffers(stream))

        print(f'cam{idx} ({cam.id}): capturing {num_bufs} buffers with {stream_config}')

        # Create the requests and assign a buffer for each request

        self.reqs = []
        self.mfbs = {}

        for i in range(num_bufs):
            # Use the buffer index as the "cookie"
            req = cam.create_request(idx)

            buffer = allocator.buffers(stream)[i]
            req.add_buffer(stream, buffer)

            self.reqs.append(req)

            # Save a mmapped buffer so we can calculate the CRC later
            self.mfbs[buffer] = libcamera.utils.MappedFrameBuffer(buffer).mmap()

    def uninit_camera(self):
        # Stop the camera

        self.cam.stop()

        # Release the camera

        self.cam.release()


# A container class for our state
class CaptureContext:
    cm: libcam.CameraManager
    camera_contexts: list[CameraCaptureContext] = []

    def handle_camera_event(self):
        # cm.get_ready_requests() returns the ready requests, which in our case
        # should almost always return a single Request, but in some cases there
        # could be multiple or none.

        reqs = self.cm.get_ready_requests()

        # Process the captured frames

        for req in reqs:
            self.handle_request(req)

        return True

    def handle_request(self, req: libcam.Request):
        cam_ctx = self.camera_contexts[req.cookie]

        buffers = req.buffers

        assert len(buffers) == 1

        # A ready Request could contain multiple buffers if multiple streams
        # were being used. Here we know we only have a single stream,
        # and we use next(iter()) to get the first and only buffer.

        stream, fb = next(iter(buffers.items()))

        # Use the MappedFrameBuffer to access the pixel data with CPU. We calculate
        # the crc for each plane.

        mfb = cam_ctx.mfbs[fb]
        crcs = [binascii.crc32(p) for p in mfb.planes]

        meta = fb.metadata

        print('cam{:<6} seq {:<6} bytes {:10} CRCs {}'
              .format(cam_ctx.idx,
                      meta.sequence,
                      '/'.join([str(p.bytes_used) for p in meta.planes]),
                      crcs))

        # We want to re-queue the buffer we just handled. Instead of creating
        # a new Request, we re-use the old one. We need to call req.reuse()
        # to re-initialize the Request before queuing.

        req.reuse()
        cam_ctx.cam.queue_request(req)

    def handle_key_event(self):
        sys.stdin.readline()
        print('Exiting...')
        return False

    def capture(self):
        # Queue the requests to the camera

        for cam_ctx in self.camera_contexts:
            for req in cam_ctx.reqs:
                cam_ctx.cam.queue_request(req)

        # Use Selector to wait for events from the camera and from the keyboard

        sel = selectors.DefaultSelector()
        sel.register(sys.stdin, selectors.EVENT_READ, self.handle_key_event)
        sel.register(self.cm.event_fd, selectors.EVENT_READ, lambda: self.handle_camera_event())

        running = True

        while running:
            events = sel.select()
            for key, mask in events:
                # If the handler return False, we should exit
                if not key.data():
                    running = False


def main():
    cm = libcam.CameraManager.singleton()

    ctx = CaptureContext()
    ctx.cm = cm

    for idx, cam in enumerate(cm.cameras):
        cam_ctx = CameraCaptureContext(cam, idx)
        ctx.camera_contexts.append(cam_ctx)

    # Start the cameras

    for cam_ctx in ctx.camera_contexts:
        cam_ctx.cam.start()

    ctx.capture()

    for cam_ctx in ctx.camera_contexts:
        cam_ctx.uninit_camera()

    return 0


if __name__ == '__main__':
    sys.exit(main())
="hl opt">.order = bayer_case[self.pattern] ''' manual blacklevel - not robust ''' if 'ov5647' in self.camName: self.blacklevel = 16 else: self.blacklevel = 64 self.blacklevel_16 = self.blacklevel << (6) return 1 ''' print metadata for debug ''' def print_meta(self): print('\nData:') print(' ver = {}'.format(self.ver)) print(' w = {}'.format(self.w)) print(' h = {}'.format(self.h)) print(' pad = {}'.format(self.pad)) print(' fmt = {}'.format(self.fmt)) print(' sigbits = {}'.format(self.sigbits)) print(' pattern = {}'.format(self.pattern)) print(' exposure = {}'.format(self.exposure)) print(' againQ8 = {}'.format(self.againQ8)) print(' againQ8_norm = {}'.format(self.againQ8_norm)) print(' camName = {}'.format(self.camName)) print(' blacklevel = {}'.format(self.blacklevel)) print(' blacklevel_16 = {}'.format(self.blacklevel_16)) return 1 """ get image from raw scanline data """ def get_image(self, raw): self.dptr = [] """ check if data is 10 or 12 bits """ if self.sigbits == 10: """ calc length of scanline """ lin_len = ((((((self.w+self.pad+3)>>2)) * 5)+31)>>5) * 32 """ stack scan lines into matrix """ raw = np.array(raw).reshape(-1, lin_len).astype(np.int64)[:self.h, ...] """ separate 5 bits in each package, stopping when w is satisfied """ ba0 = raw[..., 0:5*((self.w+3)>>2):5] ba1 = raw[..., 1:5*((self.w+3)>>2):5] ba2 = raw[..., 2:5*((self.w+3)>>2):5] ba3 = raw[..., 3:5*((self.w+3)>>2):5] ba4 = raw[..., 4:5*((self.w+3)>>2):5] """ assemble 10 bit numbers """ ch0 = np.left_shift((np.left_shift(ba0, 2) + (ba4 % 4)), 6) ch1 = np.left_shift((np.left_shift(ba1, 2) + (np.right_shift(ba4, 2) % 4)), 6) ch2 = np.left_shift((np.left_shift(ba2, 2) + (np.right_shift(ba4, 4) % 4)), 6) ch3 = np.left_shift((np.left_shift(ba3, 2) + (np.right_shift(ba4, 6) % 4)), 6) """ interleave bits """ mat = np.empty((self.h, self.w), dtype=ch0.dtype) mat[..., 0::4] = ch0 mat[..., 1::4] = ch1 mat[..., 2::4] = ch2 mat[..., 3::4] = ch3 """ There is som eleaking memory somewhere in the code. This code here seemed to make things good enough that the code would run for reasonable numbers of images, however this is techincally just a workaround. (sorry) """ ba0, ba1, ba2, ba3, ba4 = None, None, None, None, None del ba0, ba1, ba2, ba3, ba4 ch0, ch1, ch2, ch3 = None, None, None, None del ch0, ch1, ch2, ch3 """ same as before but 12 bit case """ elif self.sigbits == 12: lin_len = ((((((self.w+self.pad+1)>>1)) * 3)+31)>>5) * 32 raw = np.array(raw).reshape(-1, lin_len).astype(np.int64)[:self.h, ...] ba0 = raw[..., 0:3*((self.w+1)>>1):3] ba1 = raw[..., 1:3*((self.w+1)>>1):3] ba2 = raw[..., 2:3*((self.w+1)>>1):3] ch0 = np.left_shift((np.left_shift(ba0, 4) + ba2 % 16), 4) ch1 = np.left_shift((np.left_shift(ba1, 4) + (np.right_shift(ba2, 4)) % 16), 4) mat = np.empty((self.h, self.w), dtype=ch0.dtype) mat[..., 0::2] = ch0 mat[..., 1::2] = ch1 else: """ data is neither 10 nor 12 or incorrect data """ print('ERROR: wrong bit format, only 10 or 12 bit supported') return 0 """ separate bayer channels """ c0 = mat[0::2, 0::2] c1 = mat[0::2, 1::2] c2 = mat[1::2, 0::2] c3 = mat[1::2, 1::2] self.channels = [c0, c1, c2, c3] return 1 """ obtain 16x16 patch centred at macbeth square centre for each channel """ def get_patches(self, cen_coords, size=16): """ obtain channel widths and heights """ ch_w, ch_h = self.w, self.h cen_coords = list(np.array((cen_coords[0])).astype(np.int32)) self.cen_coords = cen_coords """ squares are ordered by stacking macbeth chart columns from left to right. Some useful patch indices: white = 3 black = 23 'reds' = 9, 10 'blues' = 2, 5, 8, 20, 22 'greens' = 6, 12, 17 greyscale = 3, 7, 11, 15, 19, 23 """ all_patches = [] for ch in self.channels: ch_patches = [] for cen in cen_coords: ''' macbeth centre is placed at top left of central 2x2 patch to account for rounding Patch pixels are sorted by pixel brightness so spatial information is lost. ''' patch = ch[cen[1]-7:cen[1]+9, cen[0]-7:cen[0]+9].flatten() patch.sort() if patch[-5] == (2**self.sigbits-1)*2**(16-self.sigbits): self.saturated = True ch_patches.append(patch) # print('\nNew Patch\n') all_patches.append(ch_patches) # print('\n\nNew Channel\n\n') self.patches = all_patches return 1 def brcm_load_image(Cam, im_str): """ Load image where raw data and metadata is in the BRCM format """ try: """ create byte array """ with open(im_str, 'rb') as image: f = image.read() b = bytearray(f) """ return error if incorrect image address """ except FileNotFoundError: print('\nERROR:\nInvalid image address') Cam.log += '\nWARNING: Invalid image address' return 0 """ return error if problem reading file """ if f is None: print('\nERROR:\nProblem reading file') Cam.log += '\nWARNING: Problem readin file' return 0 # print('\nLooking for EOI and BRCM header') """ find end of image followed by BRCM header by turning bytearray into hex string and string matching with regexp """ start = -1 match = bytearray(b'\xff\xd9@BRCM') match_str = binascii.hexlify(match) b_str = binascii.hexlify(b) """ note index is divided by two to go from string to hex """ indices = [m.start()//2 for m in re.finditer(match_str, b_str)] # print(indices) try: start = indices[0] + 3 except IndexError: print('\nERROR:\nNo Broadcom header found') Cam.log += '\nWARNING: No Broadcom header found!' return 0 """ extract data after header """ # print('\nExtracting data after header') buf = b[start:start+32768] Img = Image(buf) Img.str = im_str # print('Data found successfully') """ obtain metadata """ # print('\nReading metadata') Img.get_meta() Cam.log += '\nExposure : {} us'.format(Img.exposure) Cam.log += '\nNormalised gain : {}'.format(Img.againQ8_norm) # print('Metadata read successfully') """ obtain raw image data """ # print('\nObtaining raw image data') raw = b[start+32768:] Img.get_image(raw) """ delete raw to stop memory errors """ raw = None del raw # print('Raw image data obtained successfully') return Img def dng_load_image(Cam, im_str): try: Img = Image(None) # RawPy doesn't load all the image tags that we need, so we use py3exiv2 metadata = pyexif.ImageMetadata(im_str) metadata.read() Img.ver = 100 # random value """ The DNG and TIFF/EP specifications use different IFDs to store the raw image data and the Exif tags. DNG stores them in a SubIFD and in an Exif IFD respectively (named "SubImage1" and "Photo" by pyexiv2), while TIFF/EP stores them both in IFD0 (name "Image"). Both are used in "DNG" files, with libcamera-apps following the DNG recommendation and applications based on picamera2 following TIFF/EP. This code detects which tags are being used, and therefore extracts the correct values. """ try: Img.w = metadata['Exif.SubImage1.ImageWidth'].value subimage = "SubImage1" photo = "Photo" except KeyError: Img.w = metadata['Exif.Image.ImageWidth'].value subimage = "Image" photo = "Image" Img.pad = 0 Img.h = metadata[f'Exif.{subimage}.ImageLength'].value white = metadata[f'Exif.{subimage}.WhiteLevel'].value Img.sigbits = int(white).bit_length() Img.fmt = (Img.sigbits - 4) // 2 Img.exposure = int(metadata[f'Exif.{photo}.ExposureTime'].value * 1000000) Img.againQ8 = metadata[f'Exif.{photo}.ISOSpeedRatings'].value * 256 / 100 Img.againQ8_norm = Img.againQ8 / 256 Img.camName = metadata['Exif.Image.Model'].value Img.blacklevel = int(metadata[f'Exif.{subimage}.BlackLevel'].value[0]) Img.blacklevel_16 = Img.blacklevel << (16 - Img.sigbits) bayer_case = { '0 1 1 2': (0, (0, 1, 2, 3)), '1 2 0 1': (1, (2, 0, 3, 1)), '2 1 1 0': (2, (3, 2, 1, 0)), '1 0 2 1': (3, (1, 0, 3, 2)) } cfa_pattern = metadata[f'Exif.{subimage}.CFAPattern'].value Img.pattern = bayer_case[cfa_pattern][0] Img.order = bayer_case[cfa_pattern][1] # Now use RawPy tp get the raw Bayer pixels raw_im = raw.imread(im_str) raw_data = raw_im.raw_image shift = 16 - Img.sigbits c0 = np.left_shift(raw_data[0::2, 0::2].astype(np.int64), shift) c1 = np.left_shift(raw_data[0::2, 1::2].astype(np.int64), shift) c2 = np.left_shift(raw_data[1::2, 0::2].astype(np.int64), shift) c3 = np.left_shift(raw_data[1::2, 1::2].astype(np.int64), shift) Img.channels = [c0, c1, c2, c3] Img.rgb = raw_im.postprocess() except Exception: print("\nERROR: failed to load DNG file", im_str) print("Either file does not exist or is incompatible") Cam.log += '\nERROR: DNG file does not exist or is incompatible' raise return Img ''' load image from file location and perform calibration check correct filetype mac boolean is true if image is expected to contain macbeth chart and false if not (alsc images don't have macbeth charts) ''' def load_image(Cam, im_str, mac_config=None, show=False, mac=True, show_meta=False): """ check image is correct filetype """ if '.jpg' in im_str or '.jpeg' in im_str or '.brcm' in im_str or '.dng' in im_str: if '.dng' in im_str: Img = dng_load_image(Cam, im_str) else: Img = brcm_load_image(Cam, im_str) """ handle errors smoothly if loading image failed """ if Img == 0: return 0 if show_meta: Img.print_meta() if mac: """ find macbeth centres, discarding images that are too dark or light """ av_chan = (np.mean(np.array(Img.channels), axis=0)/(2**16)) av_val = np.mean(av_chan) # print(av_val) if av_val < Img.blacklevel_16/(2**16)+1/64: macbeth = None print('\nError: Image too dark!') Cam.log += '\nWARNING: Image too dark!' else: macbeth = find_macbeth(Cam, av_chan, mac_config) """ if no macbeth found return error """ if macbeth is None: print('\nERROR: No macbeth chart found') return 0 mac_cen_coords = macbeth[1] # print('\nMacbeth centres located successfully') """ obtain image patches """ # print('\nObtaining image patches') Img.get_patches(mac_cen_coords) if Img.saturated: print('\nERROR: Macbeth patches have saturated') Cam.log += '\nWARNING: Macbeth patches have saturated!' return 0 """ clear memory """ Img.buf = None del Img.buf # print('Image patches obtained successfully') """ optional debug """ if show and __name__ == '__main__': copy = sum(Img.channels)/2**18 copy = np.reshape(copy, (Img.h//2, Img.w//2)).astype(np.float64) copy, _ = reshape(copy, 800) represent(copy) return Img """ return error if incorrect filetype """ else: # print('\nERROR:\nInvalid file extension') return 0 """ bytearray splice to number little endian """ def ba_to_b(b): total = 0 for i in range(len(b)): total += 256**i * b[i] return total