def saveImage(self):
ueye.is_AllocImageMem(self.hcam, self.sensorinfo.nMaxWidth, self.sensorinfo.nMaxHeight, 24, self.pccmem,
self.memID)
ueye.is_SetImageMem(self.hcam, self.pccmem, self.memID)
ueye.is_SetDisplayPos(self.hcam, 100, 100)
self.nret = ueye.is_FreezeVideo(self.hcam, ueye.IS_WAIT)
self.rawImageTimeStamp = datetime.datetime.now()
self.imageTimeStamp = datetime.datetime.now().strftime('%Y_%m_%d_%H_%M_%S')
self.imageName = 'imagem_%s.jpg' % self.imageTimeStamp
self.imagePath = self.operationConfigs['savingDirectory'] + self.imageName
# self.imagePath = self.operationConfigs['savingDirectory'] + "tmp.jpg"
self.FileParams = ueye.IMAGE_FILE_PARAMS()
self.FileParams.pwchFileName = self.imagePath
self.FileParams.nFileType = ueye.IS_IMG_BMP
self.FileParams.ppcImageMem = None
self.FileParams.pnImageID = None
self.nret = ueye.is_ImageFile(self.hcam, ueye.IS_IMAGE_FILE_CMD_SAVE, self.FileParams,
ueye.sizeof(self.FileParams))
ueye.is_FreeImageMem(self.hcam, self.pccmem, self.memID)
#sleep(.01)
#ueye.is_ExitCamera(self.hcam)
self.image = np.uint8(ndimage.imread(self.imagePath, flatten=True))
self.image = self.crop_end(self.image, 0, 100)
def show_image(self):
nRet = ueye.is_InitCamera(self.h_cam, None)
nRet = ueye.is_SetDisplayMode(self.h_cam, ueye.IS_SET_DM_DIB)
nRet = ueye.is_AOI(self.h_cam, ueye.IS_AOI_IMAGE_GET_AOI, self.rectAOI,
ueye.sizeof(self.rectAOI))
self.width = self.rectAOI.s32Width
self.height = self.rectAOI.s32Height
nRet = ueye.is_AllocImageMem(self.h_cam, self.width, self.height,
self.nBitsPerPixel, self.pcImageMemory,
self.MemID)
nRet = ueye.is_SetImageMem(self.h_cam, self.pcImageMemory, self.MemID)
nRet = ueye.is_SetColorMode(self.h_cam, self.ColorMode)
nRet = ueye.is_CaptureVideo(self.h_cam, ueye.IS_DONT_WAIT)
nRet = ueye.is_InquireImageMem(self.h_cam, self.pcImageMemory,
self.MemID, self.width, self.height,
self.nBitsPerPixel, self.pitch)
while nRet == ueye.IS_SUCCESS:
array = ueye.get_data(self.pcImageMemory,
self.width,
self.height,
self.nBitsPerPixel,
self.pitch,
copy=False)
frame = np.reshape(
array,
(self.height.value, self.width.value, self.bytes_per_pixel))
frame = cv2.resize(frame, (0, 0), fx=0.5, fy=0.5)
size = (self.height, self.width)
new_camera_matrix, roi = cv2.getOptimalNewCameraMatrix(
self.camera_matrix, self.dist_coeff, size, 1, size)
dst = cv2.undistort(frame, self.camera_matrix, self.dist_coeff,
None, new_camera_matrix)
x, y, w, h = roi
self.dst = dst[y:y + h, x:x + w]
self.detect_colors()
self.extrinsic_calibration()
cv2.imshow("camera", self.dst)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
elif cv2.waitKey(1) & 0xFF == ord('t'):
cv2.imwrite("/home/lennart/dorna/camera/images/gps.bmp",
self.dst)
elif cv2.waitKey(100) & 0xFF == ord('l'):
self.found_container = False
self.container_world_position.clear()
print("Behälterposition zurückgesetzt")
ueye.is_FreeImageMem(self.h_cam, self.pcImageMemory, self.MemID)
ueye.is_ExitCamera(self.h_cam)
cv2.destroyAllWindows()
def release(self):
# Releases an image memory that was allocated using is_AllocImageMem() and removes it from the driver management
ueye.is_FreeImageMem(self.hCam, self.pcImageMemory, self.MemID)
# Disables the hCam camera handle and releases the data structures and memory areas taken up by the uEye camera
ueye.is_ExitCamera(self.hCam)
print('Camera connection closed')
def disconnect_device(self, variable=None):
ueye.is_FreeImageMem(self.hid, self.ppcImgMem, self.MemID)
ueye.is_ExitCamera(self.hid)
self.camera = False
if variable:
variable.delete(0, 'end')
self.return_devices(variable)
def __del__(self):
ueye.is_FreeImageMem(self.hCam, self.pcImageMemory, self.MemID)
# Disables the hCam camera handle and releases the data structures and memory areas taken up by the uEye camera
ueye.is_ExitCamera(self.hCam)
# Destroys the OpenCv windows
self.timeStampsFile.close()
def close_connection(self):
"""
Close the connection with the Thorlabs camera and release the handle
as well as the memory usage
"""
ueye.is_FreeImageMem(self.hcam, self.pcImageMemory, self.MemID)
ueye.is_ExitCamera(self.hcam)
print('Connection to the camera was closed')
def disconnect_device(self):
"""
Disconnect a previously connected camera.
"""
ueye.is_FreeImageMem(self.hid, self.ppcImgMem, self.MemID)
ueye.is_ExitCamera(self.hid)
self.camera = False
def main_loop():
color_trackbars()
while (CameraApi.nRet == ueye.IS_SUCCESS):
# In order to display the image in an OpenCV window we need to...
# ...extract the data of our image memory
array = ueye.get_data(CameraApi.pcImageMemory,
CameraApi.width,
CameraApi.height,
CameraApi.nBitsPerPixel,
CameraApi.pitch,
copy=False)
# ...reshape it in an numpy array...
frame = np.reshape(array,
(CameraApi.height.value, CameraApi.width.value,
CameraApi.bytes_per_pixel))
# ...resize the image by a half
# frame = cv2.resize(frame,(0,0), fx=0.5, fy=0.5)
#---------------------------------------------------------------------------------------------------------------------------------------
#Convert camera feed from BGRA to BGR
frame_to_bgr = cv2.cvtColor(frame, cv2.COLOR_BGRA2BGR)
#Apply a Gaussian blur that has 11x11 kernel size to the BGR frame
frame_to_bgr = cv2.GaussianBlur(frame_to_bgr, (5, 5), 0)
cv2.imshow("BGR Frame", frame_to_bgr)
#Convert camera feed from BGR color space to HSV color space
hsv_frame = cv2.cvtColor(frame_to_bgr, cv2.COLOR_BGR2HSV)
frame_threshold(frame_to_bgr, hsv_frame)
#---------------------------------------------------------------------------------------------------------------------------------------
# Press q if you want to end the loop
if cv2.waitKey(1) & 0xFF == ord('q'):
break
#---------------------------------------------------------------------------------------------------------------------------------------
# Releases an image memory that was allocated using is_AllocImageMem() and removes it from the driver management
ueye.is_FreeImageMem(CameraApi.hCam, CameraApi.pcImageMemory,
CameraApi.MemID)
# Disables the hCam camera handle and releases the data structures and memory areas taken up by the uEye camera
ueye.is_ExitCamera(CameraApi.hCam)
# Destroys the OpenCv windows
cv2.destroyAllWindows()
print()
print("END")
def Exit(self):
if self.KepcoInit_Switch == 1:
self.kepco_inst.write("CURR {curr}".format(curr=0))
self.kepco_inst.write("OUTP OFF")
self.Movie_Switch = -1
#time.sleep(1)
#cv2.destroyAllWindows()
ueye.is_FreeImageMem(self.hcam, self.mem_ptr, self.mem_id)
self.ret = ueye.is_ExitCamera(self.hcam)
self.close()
def setBuffer(self, size): self.bufCount=size if self.Imgs is not None: for i in range(self.bufCount): rv=ueye.is_FreeImageMem (self.hcam, self.Imgs[i], self.bufIds[i]) if rv: self.status=True return True self.bufIds[i] = 0 if self.getAOI(): self.status=True return True self.imgWidth=self.AOI.s32Width.value self.imgHeight=self.AOI.s32Height.value self.Imgs=[ueye.c_mem_p() for i in range(size)] self.bufIds=[ueye.c_int() for i in range(size)] for i in range(self.bufCount): rv=ueye.is_AllocImageMem(self.hcam, self.imgWidth, self.imgHeight,self.bitsPixel, self.Imgs[i], self.bufIds[i]) if rv: self.status=True return True rv=ueye.is_AddToSequence (self.hcam, self.Imgs[i], self.bufIds[i]) if rv: self.status=True return True self.LineInc=ueye.c_int() rv=ueye.is_GetImageMemPitch (self.hcam, self.LineInc) if rv: self.status=True return True return False
def alloc(self, buffer_count=3):
'''
Initialization of the ring buffer.
'''
rec_aoi = self.Rect(*self.get_aoi())
color_mode = ueye.is_SetColorMode(self.cam, ueye.IS_GET_COLOR_MODE)
self.bpp = get_bits_per_pixel(color_mode)
# --- freeing the memory from previous buffer --- #
for buff in self.frame_buffer:
hasWorked = ueye.is_FreeImageMem(self.cam, buff.mem_ptr,
buff.mem_id)
self.check(hasWorked, 'is_FreeImageMem')
# --- allocate memory to buffer --- #
for i in range(buffer_count):
buff = self.ImageBuffer()
ueye.is_AllocImageMem(self.cam, rec_aoi.width, rec_aoi.height,
self.bpp, buff.mem_ptr, buff.mem_id)
hasWorked = ueye.is_AddToSequence(self.cam, buff.mem_ptr,
buff.mem_id)
self.check(hasWorked, 'is_AddToSequence')
self.frame_buffer.append(buff)
# --- --- #
hasWorked = ueye.is_InitImageQueue(
self.cam, 0) # init and return the success of image queued.
self.check(hasWorked, 'is_InitImageQueue')
# --- --- #
self.img_buffer = self.frame_buffer[-1]
def alloc(self):
"""
Allocate memory for futur images.
"""
rect = self.get_aoi()
bpp = self.nBitsPerPixel
for buff in self.img_buffer:
self.nRet = ueye.is_FreeImageMem(self.cam, buff.mem_ptr, buff.mem_id)
if self.nRet != ueye.IS_SUCCESS:
error_log(self.nRet, "is_FreeImageMem")
self.img_buffer = []
for i in range(self.buffer_count):
buff = ImageBuffer()
ueye.is_AllocImageMem(self.cam,
rect.width,
rect.height,
bpp,
buff.mem_ptr,
buff.mem_id)
ueye.is_AddToSequence(self.cam, buff.mem_ptr, buff.mem_id)
self.img_buffer.append(buff)
self.nRet = ueye.is_InitImageQueue(self.cam, 0)
if self.nRet != ueye.IS_SUCCESS:
error_log(self.nRet, "is_InitImageQueue")
def give_da_stream():
hCam, sInfo, cInfo, pcImageMemory, MemID, rectAOI, pitch, nBitsPerPixel, channels, m_nColorMode, bytes_per_pixel, height, width = init_camera(
)
nRet = ueye.is_CaptureVideo(hCam, ueye.IS_DONT_WAIT)
nRet = ueye.is_InquireImageMem(hCam, pcImageMemory, MemID, width, height,
nBitsPerPixel, pitch)
try:
while (nRet == ueye.IS_SUCCESS):
# In order to display the image in an OpenCV window we need to...
# ...extract the data of our image memory
array = ueye.get_data(pcImageMemory,
width,
height,
nBitsPerPixel,
pitch,
copy=False)
# bytes_per_pixel = int(nBitsPerPixel / 8)
# ...reshape it in an numpy array...
frame = np.reshape(array,
(height.value, width.value, bytes_per_pixel))
# ...resize the image by a half
# frame = cv2.resize(frame,(0,0),fx=0.5, fy=0.5)
# Press q if you want to end the loop
# Press q if you want to end the loop
yield frame
# ---------------------------------------------------------------------------------------------------------------------------------------
# Include image data processing here
# ---------------------------------------------------------------------------------------------------------------------------------------
finally:
# Releases an image memory that was allocated using is_AllocImageMem() and removes it from the driver management
ueye.is_FreeImageMem(hCam, pcImageMemory, MemID)
# Disables the hCam camera handle and releases the data structures and memory areas taken up by the uEye camera
ueye.is_ExitCamera(hCam)
def _deallocate_memory(self):
if self._ppc_img_mem is None:
return
# Releases an image memory that was allocated using is_AllocImageMem() and removes it from the driver management
err = ueye.is_FreeImageMem(self._cam, self._ppc_img_mem, self._mem_id)
if err != ueye.IS_SUCCESS:
raise CameraException(self._cam, 'ueye>_deallocate_memory>', err)
self._ppc_img_mem = None
def saveImage(self):
try:
time1 = datetime.datetime.now()
ueye.is_AllocImageMem(self.hcam, self.sensorinfo.nMaxWidth,
self.sensorinfo.nMaxHeight, 24, self.pccmem,
self.memID)
ueye.is_SetImageMem(self.hcam, self.pccmem, self.memID)
ueye.is_SetDisplayPos(self.hcam, 100, 100)
self.nret = ueye.is_FreezeVideo(self.hcam, ueye.IS_WAIT)
self.imageTimeStamp = datetime.datetime.now().strftime(
'%Y_%m_%d_%H_%M_%S')
self.imageName = 'imagem_%s.jpg' % self.imageTimeStamp
self.imagePath = self.operationConfigs[
'savingDirectory'] + self.imageName
self.FileParams = ueye.IMAGE_FILE_PARAMS()
self.FileParams.pwchFileName = self.imagePath
self.FileParams.nFileType = ueye.IS_IMG_BMP
self.FileParams.ppcImageMem = None
self.FileParams.pnImageID = None
self.nret = ueye.is_ImageFile(self.hcam,
ueye.IS_IMAGE_FILE_CMD_SAVE,
self.FileParams,
ueye.sizeof(self.FileParams))
ueye.is_FreeImageMem(self.hcam, self.pccmem, self.memID)
sleep(.01)
ueye.is_ExitCamera(self.hcam)
time2 = datetime.datetime.now()
elapsed_time = time2 - time1
logging.info('Saved: {}! Elasped time (ms): {}'.format(
self.imageName, elapsed_time.microseconds / 1000))
self.pijuice.status.SetLedBlink('D2', 2, [0, 255, 0], 50,
[0, 255, 0], 50)
sleep(.1)
self.pijuice.status.SetLedState('D2', [0, 0, 0])
except:
logging.warning('NOT SAVED: {}!\n'.format(self.imageName))
self.pijuice.status.SetLedBlink('D2', 2, [255, 0, 0], 50,
[255, 0, 0], 50)
sleep(.1)
self.pijuice.status.SetLedState('D2', [0, 0, 0])
pass
def run(self):
a = ueye.is_InitCamera(self.hCam, None)
b = ueye.is_GetCameraInfo(self.hCam, self.cInfo)
c = ueye.is_GetSensorInfo(self.hCam, self.sInfo)
d = ueye.is_ResetToDefault(self.hCam)
e = ueye.is_SetDisplayMode(self.hCam, ueye.IS_SET_DM_DIB)
g = ueye.is_AOI(self.hCam, ueye.IS_AOI_IMAGE_GET_AOI, self.rectAOI,
ueye.sizeof(self.rectAOI))
self.width = self.rectAOI.s32Width
self.height = self.rectAOI.s32Height
h = ueye.is_AllocImageMem(self.hCam, self.width, self.height,
self.nBitsPerPixel, self.pcImageMemory,
self.MemID)
i = ueye.is_SetImageMem(self.hCam, self.pcImageMemory, self.MemID)
f = ueye.is_SetColorMode(self.hCam, ueye.IS_CM_MONO12)
ueye.is_CaptureVideo(self.hCam, ueye.IS_WAIT)
j = ueye.is_InquireImageMem(self.hCam, self.pcImageMemory, self.MemID,
self.width, self.height,
self.nBitsPerPixel, self.pitch)
self.IMAGE_FILE_PARAMS = ueye.IMAGE_FILE_PARAMS(
self.pcImageMemory, self.MemID)
self.IMAGE_FILE_PARAMS.nFileType = ueye.IS_IMG_PNG
self.k = ueye.sizeof(self.IMAGE_FILE_PARAMS)
# ueye.is_AutoParameter(self.hCam, ueye.IS_AES_CMD_SET_ENABLE, self.autoParameter, ueye.sizeof(self.autoParameter))
while self.flag:
self.data = np.ctypeslib.as_array(
ctypes.cast(self.pcImageMemory,
ctypes.POINTER(ctypes.c_ubyte)),
(self.height * self.pitch, ))
self.data.dtype = 'uint16'
self.CameraSignal.emit(self.data)
time.sleep(0.1)
ueye.is_FreeImageMem(self.hCam, self.pcImageMemory, self.MemID)
ueye.is_ExitCamera(self.hCam)
def take_picture(hCam, pcImageMemory, MemID, pitch, nBitsPerPixel,
bytes_per_pixel, height, width):
array = ueye.get_data(pcImageMemory,
width,
height,
nBitsPerPixel,
pitch,
copy=False)
frame = np.reshape(array, (height.value, width.value, bytes_per_pixel))
ueye.is_FreeImageMem(hCam, pcImageMemory, MemID)
# Disables the hCam camera handle and releases the data structures and memory areas taken up by the uEye camera
ueye.is_ExitCamera(hCam)
# Destroys the OpenCv windows
cv2.destroyAllWindows()
return frame
def DestroyBuffers(self):
self._poll = False
self.check_success(ueye.is_ExitImageQueue(self.h))
self.check_success(ueye.is_ClearSequence(self.h))
while len(self._buffers) > 0:
buffer_id, data = self._buffers.pop()
self.check_success(ueye.is_FreeImageMem(self.h, data, buffer_id))
self.free_buffers = None
self.n_full = 0
def saveImage(self):
# try:
time1 = datetime.datetime.now()
ueye.is_AllocImageMem(self.hcam, self.sensorinfo.nMaxWidth,
self.sensorinfo.nMaxHeight, 24, self.pccmem,
self.memID)
ueye.is_SetImageMem(self.hcam, self.pccmem, self.memID)
ueye.is_SetDisplayPos(self.hcam, 100, 100)
self.nret = ueye.is_FreezeVideo(self.hcam, ueye.IS_WAIT)
self.rawImageTimeStamp = datetime.datetime.now()
self.imageTimeStamp = datetime.datetime.now().strftime(
'%Y_%m_%d_%H_%M_%S')
self.imageName = 'imagem_%s.jpg' % self.imageTimeStamp
self.imagePath = self.operationConfigs[
'savingDirectory'] + self.imageName
# self.imagePath = self.operationConfigs['savingDirectory'] + "tmp.jpg"
self.FileParams = ueye.IMAGE_FILE_PARAMS()
self.FileParams.pwchFileName = self.imagePath
self.FileParams.nFileType = ueye.IS_IMG_BMP
self.FileParams.ppcImageMem = None
self.FileParams.pnImageID = None
self.nret = ueye.is_ImageFile(self.hcam, ueye.IS_IMAGE_FILE_CMD_SAVE,
self.FileParams,
ueye.sizeof(self.FileParams))
ueye.is_FreeImageMem(self.hcam, self.pccmem, self.memID)
sleep(.01)
ueye.is_ExitCamera(self.hcam)
# self.image = np.ones((self.sensorinfo.nMaxHeight.value, self.sensorinfo.nMaxWidth.value), dtype=np.uint8)
# ueye.is_CopyImageMem(self.hcam, self.pccmem, self.memID, self.image.ctypes.data)
self.image = np.uint8(ndimage.imread(self.imagePath, flatten=True))
time2 = datetime.datetime.now()
elapsed_time = time2 - time1
logging.info('Saved: {}! Elasped time (s): {}'.format(
self.imageName, elapsed_time.total_seconds()))
def saveImage(self):
try:
time1 = datetime.datetime.now()
ueye.is_AllocImageMem(self.hcam, self.sensorinfo.nMaxWidth,
self.sensorinfo.nMaxHeight, 24, self.pccmem,
self.memID)
ueye.is_SetImageMem(self.hcam, self.pccmem, self.memID)
ueye.is_SetDisplayPos(self.hcam, 100, 100)
self.nret = ueye.is_FreezeVideo(self.hcam, ueye.IS_WAIT)
self.imageTimeStamp = datetime.datetime.now().strftime(
'%Y_%m_%d_%H_%M_%S')
self.imageName = 'imagem_%s.jpg' % self.imageTimeStamp
self.imagePath = self.savingDirectory + self.imageName
self.FileParams = ueye.IMAGE_FILE_PARAMS()
self.FileParams.pwchFileName = self.imagePath
self.FileParams.nFileType = ueye.IS_IMG_BMP
self.FileParams.ppcImageMem = None
self.FileParams.pnImageID = None
self.nret = ueye.is_ImageFile(self.hcam,
ueye.IS_IMAGE_FILE_CMD_SAVE,
self.FileParams,
ueye.sizeof(self.FileParams))
# print(nret)
ueye.is_FreeImageMem(self.hcam, self.pccmem, self.memID)
sleep(.1)
ueye.is_ExitCamera(self.hcam)
time2 = datetime.datetime.now()
elapsed_time = time2 - time1
# print('Elasped time (s): {}'.format(elapsed_time))
print('Image saved at {}! Elasped time (ms) {}'.format(
self.imageTimeStamp, elapsed_time.microseconds / 1000))
except:
print('Image not saved at {}!\n'.format(self.imageTimeStamp))
pass
def alloc(self, buffer_count=3):
rect = self.get_aoi()
bpp = get_bits_per_pixel(self.get_colormode())
for buff in self.img_buffers:
check(ueye.is_FreeImageMem(self.h_cam, buff.mem_ptr, buff.mem_id))
for i in range(buffer_count):
buff = ImageBuffer()
ueye.is_AllocImageMem(self.h_cam, rect.width, rect.height, bpp,
buff.mem_ptr, buff.mem_id)
check(ueye.is_AddToSequence(self.h_cam, buff.mem_ptr, buff.mem_id))
self.img_buffers.append(buff)
ueye.is_InitImageQueue(self.h_cam, 0)
def alloc(self):
"""
Allocate memory for futur images.
"""
# Get camera settings
rect = self.get_aoi()
bpp = get_bits_per_pixel(self.get_colormode())
# Check that already existing buffers are free
for buff in self.img_buffers:
check(ueye.is_FreeImageMem(self.h_cam, buff.mem_ptr, buff.mem_id))
self.img_buffers = []
# Create asked buffers
for i in range(self.buffer_count):
buff = ImageBuffer()
ueye.is_AllocImageMem(self.h_cam, rect.width, rect.height, bpp,
buff.mem_ptr, buff.mem_id)
check(ueye.is_AddToSequence(self.h_cam, buff.mem_ptr, buff.mem_id))
self.img_buffers.append(buff)
# Check that ...
ueye.is_InitImageQueue(self.h_cam, 0)
#...and finally display it
cv2.imshow("SimpleLive_Python_uEye_OpenCV", frame2)
# Press q if you want to end the loop
if cv2.waitKey(1):
nRet = ueye.is_FreezeVideo(hCam, ueye.IS_WAIT)
nRet1= ueye.is_GetImageInfo(hCam,MemID, Iinfo, ueye.sizeof(Iinfo) )
print(Iinfo.TimestampSystem.wSecond.value)
if cv2.waitKey(1) & 0xFF == ord('s'):
string="Cal"+str(n)+".jpg"
cv2.imwrite(string, frame)
n=n+1
if cv2.waitKey(1) & 0xFF == ord('q'):
break
#---------------------------------------------------------------------------------------------------------------------------------------
# Releases an image memory that was allocated using is_AllocImageMem() and removes it from the driver management
ueye.is_FreeImageMem(hCam, pcImageMemory, MemID)
# Disables the hCam camera handle and releases the data structures and memory areas taken up by the uEye camera
ueye.is_ExitCamera(hCam)
# Destroys the OpenCv windows
cv2.destroyAllWindows()
print()
print("END")
# Cameras' id
id = [1, 2, 3]
dev = ["Camera" + str(id[0]), "Camera" + str(id[1]), "Camera" + str(id[2])]
# Initialize Cameras with specific id
Cam0 = camera.Cam(id[0], 10)
# Setup cameras
Cam0.Setup()
p = tc.Capture_Thread(Cam0)
p.start()
# Continuous capture and saving of the image
while Cam0.nRet == ueye.IS_SUCCESS:
try:
if not p.joined:
p.join()
print("p joined")
except KeyboardInterrupt:
p.kill()
break
# Releases an image memory that was allocated using is_AllocImageMem() and removes it from the driver management
ueye.is_FreeImageMem(Cam0.cam, Cam0.pcImageMemory, Cam0.MemID)
Cam0.exit()
#Calibrate camera
tmp = calib()
while(count < 5):
cv2.waitKey(100)
count+=1
display()
cv2.waitKey(0)
(blue_xiyi, blue_angle, green_xiyi, green_angle) = markers_cycle_horizontal()
if blue_xiyi is None or green_xiyi:
#Clean-up
cv2.destroyAllWindows()
ueye.is_FreeImageMem(hcam, mem_ptr, mem_id)
ueye.is_StopLiveVideo(hcam, ueye.IS_FORCE_VIDEO_STOP)
ueye.is_ExitCamera(hcam)
cmd.event('go_init')
exit()
# (..........)
# (..........)
# (..........)
# (..........)
# (..........)
#Clean-up
cv2.destroyAllWindows()
ueye.is_FreeImageMem(hcam, mem_ptr, mem_id)
print(wertSet)
help(ueye.is_Exposure)
wert = ueye.c_double()
sizeo = ueye.sizeof(wert)
nret = ueye.is_Exposure(hcam, ueye.IS_EXPOSURE_CMD_GET_EXPOSURE, wert, sizeo)
print(wert)
nret = ueye.is_FreezeVideo(hcam, ueye.IS_WAIT)
print(nret)
FileParams = ueye.IMAGE_FILE_PARAMS()
FileParams.pwchFileName = "c:\python-test-image.png"
FileParams.nFileType = ueye.IS_IMG_PNG
FileParams.ppcImageMem = None
FileParams.pnImageID = None
nret = ueye.is_ImageFile(hcam, ueye.IS_IMAGE_FILE_CMD_SAVE, FileParams,
ueye.sizeof(FileParams))
print(nret)
nret = ueye.is_FreezeVideo(hcam, ueye.IS_WAIT)
print(nret)
FileParams = ueye.IMAGE_FILE_PARAMS()
FileParams.pwchFileName = "c:\python-test-image1.png"
FileParams.nFileType = ueye.IS_IMG_PNG
FileParams.ppcImageMem = None
FileParams.pnImageID = None
nret = ueye.is_ImageFile(hcam, ueye.IS_IMAGE_FILE_CMD_SAVE, FileParams,
ueye.sizeof(FileParams))
print(nret)
ueye.is_FreeImageMem(hcam, pccmem, memID)
ueye.is_ExitCamera(hcam)
def close(self):
ueye.is_FreeImageMem(self.input, self.mem_image, self.mem_id)
ueye.is_ExitCamera(self.input)
def show_image(self):
# Kamera initialisieren
nRet = ueye.is_InitCamera(self.h_cam, None)
nRet = ueye.is_SetDisplayMode(self.h_cam, ueye.IS_SET_DM_DIB)
nRet = ueye.is_AOI(self.h_cam, ueye.IS_AOI_IMAGE_GET_AOI, self.rectAOI,
ueye.sizeof(self.rectAOI))
self.width = self.rectAOI.s32Width
self.height = self.rectAOI.s32Height
nRet = ueye.is_AllocImageMem(self.h_cam, self.width, self.height,
self.nBitsPerPixel, self.pcImageMemory,
self.MemID)
nRet = ueye.is_SetImageMem(self.h_cam, self.pcImageMemory, self.MemID)
nRet = ueye.is_SetColorMode(self.h_cam, self.ColorMode)
nRet = ueye.is_CaptureVideo(self.h_cam, ueye.IS_DONT_WAIT)
nRet = ueye.is_InquireImageMem(self.h_cam, self.pcImageMemory,
self.MemID, self.width, self.height,
self.nBitsPerPixel, self.pitch)
while nRet == ueye.IS_SUCCESS:
# Daten der Kamera auslesen
array = ueye.get_data(self.pcImageMemory,
self.width,
self.height,
self.nBitsPerPixel,
self.pitch,
copy=False)
# Bild zuschneiden
frame = np.reshape(
array,
(self.height.value, self.width.value, self.bytes_per_pixel))
frame = cv2.resize(frame, (0, 0), fx=0.5, fy=0.5)
size = (self.height, self.width)
# optimale Kameramatrix erstellen
self.new_camera_matrix, roi = cv2.getOptimalNewCameraMatrix(
self.camera_matrix, self.dist_coeff, size, 1, size)
# Bild entzerren
dst = cv2.undistort(frame, self.camera_matrix, self.dist_coeff,
None, self.new_camera_matrix)
x, y, w, h = roi
self.dst = dst[y:y + h, x:x + w]
# Farbmasken erstellen
self.blue.create_color_mask(self.dst, self.found_blue_container)
self.red.create_color_mask(self.dst, self.found_red_container)
self.green.create_color_mask(self.dst, self.found_green_container)
# Kamera extrinsisch kalibrieren
self.extrinsic_calibration()
# Bild auf dem Bildschirm ausgeben
cv2.imshow("camera", self.dst)
# mit q Kamera schließen
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# mit t Bild aufnehemen
elif cv2.waitKey(100) & 0xFF == ord('t'):
cv2.imwrite(self.path_images + "image.bmp", self.dst)
print("Bild aufgenommen")
# mit l Position der Behälter zurücksetzen
elif cv2.waitKey(100) & 0xFF == ord('l'):
self.found_blue_container = False
self.found_red_container = False
self.found_green_container = False
print("Behälterposition zurückgesetzt")
ueye.is_FreeImageMem(self.h_cam, self.pcImageMemory, self.MemID)
ueye.is_ExitCamera(self.h_cam)
cv2.destroyAllWindows()
def ueye_free_image_mem(hcam, membuf, memid) -> None:
ueye.is_FreeImageMem(hcam, membuf, memid)
def main():
from pyueye import ueye
import numpy as np
import cv2
import sys
import os
import tensorflow as tf
import SoundTheAlarm
import time
# ---------------------------------------------------------------------------------------------------------------------------------------
# This is needed since the notebook is stored in the object_detection folder.
sys.path.append("..")
# Import utilites
from utils import label_map_util
from utils import visualization_utils as vis_util
# Name of the directory containing the object detection module we're using
MODEL_NAME = 'inference_graph'
# Grab path to current working directory
CWD_PATH = os.getcwd()
# Path to frozen detection graph .pb file, which contains the model that is used
# for object detection.
PATH_TO_CKPT = os.path.join(CWD_PATH, MODEL_NAME, 'frozen_inference_graph.pb')
# Path to label map file
PATH_TO_LABELS = os.path.join(CWD_PATH, 'training', 'labelmap.pbtxt')
# Number of classes the object detector can identify
NUM_CLASSES = 3
## Load the label map.
# Label maps map indices to category names, so that when our convolution
# network predicts `5`, we know that this corresponds to `king`.
# Here we use internal utility functions, but anything that returns a
# dictionary mapping integers to appropriate string labels would be fine
label_map = label_map_util.load_labelmap(PATH_TO_LABELS)
categories = label_map_util.convert_label_map_to_categories(label_map, max_num_classes=NUM_CLASSES,
use_display_name=True)
category_index = label_map_util.create_category_index(categories)
# Load the Tensorflow model into memory.
detection_graph = tf.Graph()
with detection_graph.as_default():
od_graph_def = tf.GraphDef()
with tf.gfile.GFile(PATH_TO_CKPT, 'rb') as fid:
serialized_graph = fid.read()
od_graph_def.ParseFromString(serialized_graph)
tf.import_graph_def(od_graph_def, name='')
sess = tf.Session(graph=detection_graph)
# Define input and output tensors (i.e. data) for the object detection classifier
# Input tensor is the image
image_tensor = detection_graph.get_tensor_by_name('image_tensor:0')
# Output tensors are the detection boxes, scores, and classes
# Each box represents a part of the image where a particular object was detected
detection_boxes = detection_graph.get_tensor_by_name('detection_boxes:0')
# Each score represents level of confidence for each of the objects.
# The score is shown on the result image, together with the class label.
detection_scores = detection_graph.get_tensor_by_name('detection_scores:0')
detection_classes = detection_graph.get_tensor_by_name('detection_classes:0')
# Number of objects detected
num_detections = detection_graph.get_tensor_by_name('num_detections:0')
# Variables
hCam = ueye.HIDS(0) # 0: first available camera; 1-254: The camera with the specified camera ID
sInfo = ueye.SENSORINFO()
cInfo = ueye.CAMINFO()
pcImageMemory = ueye.c_mem_p()
MemID = ueye.int()
rectAOI = ueye.IS_RECT()
pitch = ueye.INT()
nBitsPerPixel = ueye.INT(24) # 24: bits per pixel for color mode; take 8 bits per pixel for monochrome
channels = 3 # 3: channels for color mode(RGB); take 1 channel for monochrome
m_nColorMode = ueye.INT() # Y8/RGB16/RGB24/REG32
ueye.is_SetColorMode(hCam, ueye.IS_CM_BGR8_PACKED)
bytes_per_pixel = int(nBitsPerPixel / 8)
# ---------------------------------------------------------------------------------------------------------------------------------------
print("START")
print()
# Starts the driver and establishes the connection to the camera
nRet = ueye.is_InitCamera(hCam, None)
if nRet != ueye.IS_SUCCESS:
print("is_InitCamera ERROR")
# Reads out the data hard-coded in the non-volatile camera memory and writes it to the data structure that cInfo points to
nRet = ueye.is_GetCameraInfo(hCam, cInfo)
if nRet != ueye.IS_SUCCESS:
print("is_GetCameraInfo ERROR")
# You can query additional information about the sensor type used in the camera
nRet = ueye.is_GetSensorInfo(hCam, sInfo)
if nRet != ueye.IS_SUCCESS:
print("is_GetSensorInfo ERROR")
nRet = ueye.is_ResetToDefault(hCam)
if nRet != ueye.IS_SUCCESS:
print("is_ResetToDefault ERROR")
# Set display mode to DIB
nRet = ueye.is_SetDisplayMode(hCam, ueye.IS_SET_DM_DIB)
# Set the right color mode
if int.from_bytes(sInfo.nColorMode.value, byteorder='big') == ueye.IS_COLORMODE_BAYER:
# setup the color depth to the current windows setting
ueye.is_GetColorDepth(hCam, nBitsPerPixel, m_nColorMode)
bytes_per_pixel = int(nBitsPerPixel / 8)
print("IS_COLORMODE_BAYER: ", )
print("\tm_nColorMode: \t\t", m_nColorMode)
print("\tnBitsPerPixel: \t\t", nBitsPerPixel)
print("\tbytes_per_pixel: \t\t", bytes_per_pixel)
print()
elif int.from_bytes(sInfo.nColorMode.value, byteorder='big') == ueye.IS_COLORMODE_CBYCRY:
# for color camera models use RGB32 mode
m_nColorMode = ueye.IS_CM_BGRA8_PACKED
nBitsPerPixel = ueye.INT(32)
bytes_per_pixel = int(nBitsPerPixel / 8)
print("IS_COLORMODE_CBYCRY: ", )
print("\tm_nColorMode: \t\t", m_nColorMode)
print("\tnBitsPerPixel: \t\t", nBitsPerPixel)
print("\tbytes_per_pixel: \t\t", bytes_per_pixel)
print()
elif int.from_bytes(sInfo.nColorMode.value, byteorder='big') == ueye.IS_COLORMODE_MONOCHROME:
# for color camera models use RGB32 mode
m_nColorMode = ueye.IS_CM_MONO8
nBitsPerPixel = ueye.INT(8)
bytes_per_pixel = int(nBitsPerPixel / 8)
print("IS_COLORMODE_MONOCHROME: ", )
print("\tm_nColorMode: \t\t", m_nColorMode)
print("\tnBitsPerPixel: \t\t", nBitsPerPixel)
print("\tbytes_per_pixel: \t\t", bytes_per_pixel)
print()
else:
# for monochrome camera models use Y8 mode
m_nColorMode = ueye.IS_CM_MONO8
nBitsPerPixel = ueye.INT(8)
bytes_per_pixel = int(nBitsPerPixel / 8)
print("else")
# Can be used to set the size and position of an "area of interest"(AOI) within an image
nRet = ueye.is_AOI(hCam, ueye.IS_AOI_IMAGE_GET_AOI, rectAOI, ueye.sizeof(rectAOI))
if nRet != ueye.IS_SUCCESS:
print("is_AOI ERROR")
width = rectAOI.s32Width
height = rectAOI.s32Height
# Prints out some information about the camera and the sensor
print("Camera model:\t\t", sInfo.strSensorName.decode('utf-8'))
print("Camera serial no.:\t", cInfo.SerNo.decode('utf-8'))
print("Maximum image width:\t", width)
print("Maximum image height:\t", height)
print()
# ---------------------------------------------------------------------------------------------------------------------------------------
# Allocates an image memory for an image having its dimensions defined by width and height and its color depth defined by nBitsPerPixel
nRet = ueye.is_AllocImageMem(hCam, width, height, nBitsPerPixel, pcImageMemory, MemID)
if nRet != ueye.IS_SUCCESS:
print("is_AllocImageMem ERROR")
else:
# Makes the specified image memory the active memory
nRet = ueye.is_SetImageMem(hCam, pcImageMemory, MemID)
if nRet != ueye.IS_SUCCESS:
print("is_SetImageMem ERROR")
else:
# Set the desired color mode
nRet = ueye.is_SetColorMode(hCam, m_nColorMode)
# Activates the camera's live video mode (free run mode)
nRet = ueye.is_CaptureVideo(hCam, ueye.IS_DONT_WAIT)
if nRet != ueye.IS_SUCCESS:
print("is_CaptureVideo ERROR")
# Enables the queue mode for existing image memory sequences
nRet = ueye.is_InquireImageMem(hCam, pcImageMemory, MemID, width, height, nBitsPerPixel, pitch)
if nRet != ueye.IS_SUCCESS:
print("is_InquireImageMem ERROR")
else:
print("Press q to leave the programm")
# -----------------------------------start image loop---------------------------------------------------------------
# Continuous image display
while (nRet == ueye.IS_SUCCESS):
# In order to display the image in an OpenCV window we need to...
# ...extract the data of our image memory
array = ueye.get_data(pcImageMemory, width, height, nBitsPerPixel, pitch, copy=False)
# bytes_per_pixel = int(nBitsPerPixel / 8)
# ...reshape it in an numpy array...
frame = np.reshape(array, (height.value, width.value, bytes_per_pixel))
frame = cv2.cvtColor(frame, cv2.COLOR_GRAY2BGR)
# ------------------------------------------network_run---------------------------------------------------------
frame_expanded = np.expand_dims(frame, axis=0)
# Perform the actual detection by running the model with the image as input
(boxes, scores, classes, num) = sess.run(
[detection_boxes, detection_scores, detection_classes, num_detections],
feed_dict={image_tensor: frame_expanded})
# print("check this point-2")
# Draw the results of the detection (aka 'visualize the results')
vis_util.visualize_boxes_and_labels_on_image_array(
frame,
np.squeeze(boxes),
np.squeeze(classes).astype(np.int32),
np.squeeze(scores),
category_index,
use_normalized_coordinates=True,
line_thickness=8,
min_score_thresh=0.85)
counter = []
add = 0
while add < (NUM_CLASSES + 1):
counter.append(0)
add += 1
element = 0 # i used this loop to configure the alarm
for i in classes[0]: # it uses the variables to count how many of each object appear in each image
if (scores[0][element]) > 0.85: #=min_score_thresh # use it to feed an alarm detector script based on
counter[int(i)] += 1 # what "should" and "shouldn't" appear
element += 1
else:
break #the break stops from iterating through the entire array, which is uneccessary
####---the alarm protocol---####
#if counter[2] and counter[3]:
#if not counter[1]:
#SoundTheAlarm.sound_loop()
print("number of each class", counter)
# All the results have been drawn on the frame, so it's time to display it.
frame = cv2.resize(frame, None, fx=0.5, fy=0.5)
cv2.destroyAllWindows()
# --------------------------------------------------------------------------------------------------------------
# ...and finally display it
cv2.imshow("SimpleLive_Python_uEye_OpenCV", frame)
# Press q if you want to end the loop
if cv2.waitKey(1) & 0xFF == ord('q'):
break
time.sleep(0.5)
# ------------------------------------------------------------------------------------------------------------------
# Releases an image memory that was allocated using is_AllocImageMem() and removes it from the driver management
ueye.is_FreeImageMem(hCam, pcImageMemory, MemID)
# Disables the hCam camera handle and releases the data structures and memory areas taken up by the uEye camera
ueye.is_ExitCamera(hCam)
# Destroys the OpenCv windows
cv2.destroyAllWindows()
print()
print("END")