def main():
res = ncc.load_fw("./moviUsbBoot", "fw/flicRefApp.mvcmd")
if res < 0:
printf('load firmware error!')
sys.exit(1)
print("get usb %d sdk versin %s" % (ncc.get_usb_version(), ncc.get_sdk_version()))
print("get fw version: %s and ncc id %s" % (ncc.camera_get_fw_version(),
ncc.camera_get_ncc_id()))
sensors = ncc.CameraSensor()
sensor1 = ncc.SensorModesConfig()
if sensors.GetFirstSensor(sensor1) == 0:
print("camera: %s, %dX%d@%dfps, AFmode:%d, maxEXP:%dus,gain[%d, %d]\n" % (
sensor1.moduleName, sensor1.camWidth, sensor1.camHeight, sensor1.camFps,
sensor1.AFmode, sensor1.maxEXP, sensor1.minGain, sensor1.maxGain))
sensor2 = ncc.SensorModesConfig()
while sensors.GetNextSensor(sensor2) == 0:
print("camera: %s, %dX%d@%dfps, AFmode:%d, maxEXP:%dus,gain[%d, %d]\n" % (
sensor2.moduleName, sensor2.camWidth, sensor2.camHeight, sensor2.camFps,
sensor2.AFmode, sensor2.maxEXP, sensor2.minGain, sensor2.maxGain))
ncc.camera_select_sensor(0) # 0 1080p 1 4k
cameraCfg = sensor1
net1_info = ncc.Network1Par()
net1_info.inputFormat = ncc.IMG_FORMAT_BGR_PLANAR
net1_info.meanValue = [0.0, 0.0, 0.0]
net1_info.stdValue = 1
net1_info.isOutputYUV = 1
net1_info.isOutputH26X = 1
net1_info.isOutputJPEG = 1
net1_info.imageWidth = cameraCfg.camWidth
net1_info.imageHeight = cameraCfg.camHeight
net1_info.startX = 0
net1_info.startY = 0
net1_info.endX = cameraCfg.camWidth
net1_info.endY = cameraCfg.camHeight
net1_info.inputDimWidth = 300
net1_info.inputDimHeight = 300
# extInputs = np.zeros(ncc.MAX_EXTINPUT_SIZE,dtype = np.uint8)
# print('input size {}'.format(extInputs.size))
net1_info.extInputs = [0] * ncc.MAX_EXTINPUT_SIZE # tobytes()
net1_info.modelCascade = 1
net1_info.inferenceACC = 1
net2_info = ncc.Network2Par()
net2_info.startXAdj = -5
net2_info.startYAdj = -5
net2_info.endXAdj = 5
net2_info.endYAdj = 5
labelMask = [0]*ncc.MAX_LABEL_SIZE
labelMask[2]=1
net2_info.labelMask = labelMask
net2_info.minConf = 0.7
net2_info.inputDimWidth = 94
net2_info.inputDimHeight = 24
net2_info.inputFormat = ncc.IMG_FORMAT_BGR_PLANAR
net2_info.meanValue = [0.0, 0.0, 0.0]
net2_info.stdValue = 1
count=ncc.MAX_EXTINPUT_SIZE//2
extInputs = array('h',[0]*count)
extInputs[0] = int(ncc.f32Tof16(0))
for i in range(1, 88):
extInputs[i] = int(ncc.f32Tof16(1.0))
net2_info.extInputs = extInputs.tobytes()
net2_info.modelCascade = 0
print("input 0={} 1={} type={}".format(int(ncc.f32Tof16(1.0)),extInputs[1],type(extInputs[1])));
blob1 = "./blob/2020.3/vehicle-license-plate-detection-barrier-0106/vehicle-license-plate-detection-barrier-0106.blob";
blob2 = "./blob/2020.3/license-plate-recognition-barrier-0001/license-plate-recognition-barrier-0001.blob"; # if par_Len=0 , cal param_size auto
ret = ncc.sdk_net2_init(None, None, \
blob1, net1_info, 0, \
blob2, net2_info, 0)
metasize = 2 * 1024 * 1024
print("xlink_init ret=%d %d" % (ret, metasize))
if (ret < 0):
return
oft_x = net1_info.startX
oft_y = net1_info.startY
dis_w = net1_info.endX - net1_info.startX
dis_h = net1_info.endY - net1_info.startY
offset = struct.calcsize(media_head) # 64
size = cameraCfg.camWidth * cameraCfg.camHeight * 2
yuvbuf = bytearray(size + offset)
metabuf = bytearray(metasize)
ncc.camera_video_out(ncc.YUV420p, ncc.VIDEO_OUT_CONTINUOUS)
bmeta=False;
while (True):
size = ncc.GetYuvData(yuvbuf)
if (size <= 0):
time.sleep(0.1) # 0.1 second
continue
numarry = np.array(yuvbuf[offset:size]) # skip head frameSpecOut 64 bytes
# print("buf len=%d/%d" % (numarry.size,size))
yuv = numarry.reshape((int(cameraCfg.camHeight * 3 / 2), cameraCfg.camWidth))
bgr = cv2.cvtColor(yuv, cv2.COLOR_YUV2BGR_I420, 3)
size, outsize0,outsize1,item_num = ncc.GetMetaDataExt(metabuf)
if (size > 0)and (item_num>0):
bmeta=True
#if(bmeta):
print("ret=%d size0=%d size1=%d,num=%d" %(size,outsize0,outsize1,item_num ))
# spec=metabuf[0:offset]
#type1,seq,m_size=get_header_info(metabuf[0:offset])
#print("meta type=%d seq=%d size=%d" % (type1,seq,m_size))
#f = open("sample.txt", "wb")
#f.write(metabuf)
#f.close()
from_i=offset + ncc.OUTPUT_INDEX_SIZE
count=outsize0//2
detMetadata = struct.unpack('H'*count,metabuf[from_i:from_i+outsize0])
from_i+=outsize0 #skip output 0
count=outsize1//2
#print("out1 count %d from %d to %d" % (count,from_i,size))
secondMeta= struct.unpack('H'*count*item_num,metabuf[from_i:size])
for i in range(item_num):
image_id = int(ncc.f16Tof32(detMetadata[i * 7 + 0]))
if (image_id < 0):
break
label = int(ncc.f16Tof32(detMetadata[i * 7 + 1]))
score = ncc.f16Tof32(detMetadata[i * 7 + 2])
x0 = ncc.f16Tof32(detMetadata[i * 7 + 3])
y0 = ncc.f16Tof32(detMetadata[i * 7 + 4])
x1 = ncc.f16Tof32(detMetadata[i * 7 + 5])
y1 = ncc.f16Tof32(detMetadata[i * 7 + 6])
# print("item sise=%d score:%.2f<->min:%.2f rec:(%.3f,%.3f)<->(%.3f,%.3f) " %(item_num,score,min_score,x0,y0,x1,y1))
if ((not coordinate_is_valid(x0, y0, x1, y1)) or (score < min_score) or (labelMask[label]==0)):
continue
x = int(x0 * dis_w + oft_x)
y = int(y0 * dis_h + oft_y)
w = int((x1 - x0) * dis_w)
h = int((y1 - y0) * dis_h)
cv2.rectangle(bgr, (x, y), (x + w, y + h), (255, 128, 128), 2)
regMetadata=secondMeta[i*count:i*count+count]
regRet = array('i')
for j in range(88):
regRet.append(int(ncc.f16Tof32(regMetadata[j])))
items = [
"0", "1", "2", "3", "4", "5", "6", "7", "8", "9", \
"<Anhui>", "<Beijing>", "<Chongqing>", "<Fujian>", \
"<Gansu>", "<Guangdong>", "<Guangxi>", "<Guizhou>", \
"<Hainan>", "<Hebei>", "<Heilongjiang>", "<Henan>", \
"<HongKong>", "<Hubei>", "<Hunan>", "<InnerMongolia>", \
"<Jiangsu>", "<Jiangxi>", "<Jilin>", "<Liaoning>", \
"<Macau>", "<Ningxia>", "<Qinghai>", "<Shaanxi>", \
"<Shandong>", "<Shanghai>", "<Shanxi>", "<Sichuan>", \
"<Tianjin>", "<Tibet>", "<Xinjiang>", "<Yunnan>", \
"<Zhejiang>", "<police>", \
"A", "B", "C", "D", "E", "F", "G", "H", "I", "J", \
"K", "L", "M", "N", "O", "P", "Q", "R", "S", "T", \
"U", "V", "W", "X", "Y", "Z" \
];
result = ''
for j in range(0, len(regRet)):
if (regRet[j] == -1):
break
#result = result.join(items[regRet[j]])
result = result+items[regRet[j]]
cv2.putText(bgr, result, (x, y - 20), cv2.FONT_HERSHEY_COMPLEX, 1, (0, 0, 255), 1)
img_scaled = cv2.resize(bgr, None, fx=0.7, fy=0.7, interpolation=cv2.INTER_CUBIC)
cv2.namedWindow('openncc', cv2.WINDOW_AUTOSIZE)
cv2.imshow('openncc', img_scaled)
if (cv2.waitKey(20) == 27):
break
ncc.sdk_uninit()
cv2.destroyAllWindows()
def main():
res = ncc.load_fw("./moviUsbBoot", "fw/flicRefApp.mvcmd")
if res < 0:
printf('load firmware error!')
sys.exit(1)
print("get usb %d sdk versin %s" %
(ncc.get_usb_version(), ncc.get_sdk_version()))
print("get fw version: %s and ncc id %s" %
(ncc.camera_get_fw_version(), ncc.camera_get_ncc_id()))
sensors = ncc.CameraSensor()
sensor1 = ncc.SensorModesConfig()
if sensors.GetFirstSensor(sensor1) == 0:
print(
"camera: %s, %dX%d@%dfps, AFmode:%d, maxEXP:%dus,gain[%d, %d]\n" %
(sensor1.moduleName, sensor1.camWidth, sensor1.camHeight,
sensor1.camFps, sensor1.AFmode, sensor1.maxEXP, sensor1.minGain,
sensor1.maxGain))
sensor2 = ncc.SensorModesConfig()
while sensors.GetNextSensor(sensor2) == 0:
print(
"camera: %s, %dX%d@%dfps, AFmode:%d, maxEXP:%dus,gain[%d, %d]\n" %
(sensor2.moduleName, sensor2.camWidth, sensor2.camHeight,
sensor2.camFps, sensor2.AFmode, sensor2.maxEXP, sensor2.minGain,
sensor2.maxGain))
ncc.camera_select_sensor(0) #0 1080p 1 4k
cameraCfg = sensor1
cam_info = ncc.CameraInfo()
cam_info.inputFormat = ncc.IMG_FORMAT_BGR_PLANAR
#cam_info.meanValue = [float(0.0)]*3
cam_info.stdValue = 1
cam_info.isOutputYUV = 1
cam_info.isOutputH26X = 1
cam_info.isOutputJPEG = 1
cam_info.imageWidth = cameraCfg.camWidth
cam_info.imageHeight = cameraCfg.camHeight
cam_info.startX = 0
cam_info.startY = 0
cam_info.endX = cameraCfg.camWidth
cam_info.endY = cameraCfg.camHeight
cam_info.inputDimWidth = 0
cam_info.inputDimHeight = 0
ncc.SetMeanValue(cam_info, 0.0, 0.0, 0.0)
ret = ncc.sdk_init(
None, None,
"./blob/2020.3/face-detection-retail-0004/face-detection-retail-0004.blob",
cam_info, struct.calcsize("13I4f")) #struct CameraInfo
metasize = ncc.get_meta_size()
print("xlink_init ret=%d %d" % (ret, metasize))
if (ret < 0):
return
oft_x = cam_info.startX
oft_y = cam_info.startY
dis_w = cam_info.endX - cam_info.startX
dis_h = cam_info.endY - cam_info.startY
offset = struct.calcsize(media_head)
size = cameraCfg.camWidth * cameraCfg.camHeight * 2
yuvbuf = bytearray(size + offset)
metabuf = bytearray(metasize + offset)
ncc.camera_video_out(ncc.YUV420p, ncc.VIDEO_OUT_CONTINUOUS)
while (True):
size = ncc.GetYuvData(yuvbuf)
if (size <= 0):
time.sleep(0.1) #0.1 second
continue
numarry = np.array(
yuvbuf[offset:size]) #skip head frameSpecOut 64 bytes
#print("buf len=%d/%d" % (numarry.size,size))
yuv = numarry.reshape(
(int(cameraCfg.camHeight * 3 / 2), cameraCfg.camWidth))
bgr = cv2.cvtColor(yuv, cv2.COLOR_YUV2BGR_I420, 3)
size = ncc.GetMetaData(metabuf)
if (size > 0):
#spec=metabuf[0:offset]
#print(spec)
#type,seq,size=get_header_info(metabuf[0:offset])
#print("meta type=%d seq=%d size=%d" % (type,seq,size))
barray = metabuf[offset + ncc.OUTPUT_INDEX_SIZE:size]
#print("meta len=%d/%d" % (len(barray),size))
#print_hex(barray[0:14])
count = len(barray) // 2
sarry = struct.unpack('H' * count, barray)
#print(sarry[0:7])
for i in range(100):
image_id = ncc.f16Tof32(sarry[i * 7 + 0])
#print("face id %d" % image_id)
if (image_id < 0):
break
score = ncc.f16Tof32(sarry[i * 7 + 2])
x0 = ncc.f16Tof32(sarry[i * 7 + 3])
y0 = ncc.f16Tof32(sarry[i * 7 + 4])
x1 = ncc.f16Tof32(sarry[i * 7 + 5])
y1 = ncc.f16Tof32(sarry[i * 7 + 6])
#print("score:%.2f<->min:%.2f rec:(%.3f,%.3f)<->(%.3f,%.3f) " %(score,min_score,x0,y0,x1,y1))
if ((not coordinate_is_valid(x0, y0, x1, y1))
or (score < min_score)):
continue
x = int(x0 * dis_w + oft_x)
y = int(y0 * dis_h + oft_y)
w = int((x1 - x0) * dis_w)
h = int((y1 - y0) * dis_h)
cv2.rectangle(bgr, (x, y), (x + w, y + h), (0, 255, 0), 2)
result = ("score:%d") % (int(100 * score))
#print("%d,%d[%dx%d] score:%s" %(x,y,w,h,result))
cv2.putText(bgr, result, (x, y + 32), cv2.FONT_HERSHEY_COMPLEX,
1, (255, 0, 0), 1)
img_scaled = cv2.resize(bgr,
None,
fx=0.7,
fy=0.7,
interpolation=cv2.INTER_CUBIC)
cv2.namedWindow('openncc', cv2.WINDOW_AUTOSIZE)
cv2.imshow('openncc', img_scaled)
if (cv2.waitKey(20) == 27): break
ncc.sdk_uninit()
cv2.destroyAllWindows()
def main():
global faceLib
res = ncc.load_fw("./moviUsbBoot", "fw/flicRefApp.mvcmd")
if res < 0:
printf('load firmware error!')
sys.exit(1)
print("get usb %d sdk versin %s" %
(ncc.get_usb_version(), ncc.get_sdk_version()))
print("get fw version: %s and ncc id %s" %
(ncc.camera_get_fw_version(), ncc.camera_get_ncc_id()))
sensors = ncc.CameraSensor()
sensor1 = ncc.SensorModesConfig()
if sensors.GetFirstSensor(sensor1) == 0:
print(
"camera: %s, %dX%d@%dfps, AFmode:%d, maxEXP:%dus,gain[%d, %d]\n" %
(sensor1.moduleName, sensor1.camWidth, sensor1.camHeight,
sensor1.camFps, sensor1.AFmode, sensor1.maxEXP, sensor1.minGain,
sensor1.maxGain))
sensor2 = ncc.SensorModesConfig()
while sensors.GetNextSensor(sensor2) == 0:
print(
"camera: %s, %dX%d@%dfps, AFmode:%d, maxEXP:%dus,gain[%d, %d]\n" %
(sensor2.moduleName, sensor2.camWidth, sensor2.camHeight,
sensor2.camFps, sensor2.AFmode, sensor2.maxEXP, sensor2.minGain,
sensor2.maxGain))
ncc.camera_select_sensor(0) # 0 1080p 1 4k
cameraCfg = sensor1
net1_info = ncc.Network1Par()
net1_info.inputFormat = ncc.IMG_FORMAT_BGR_PLANAR
net1_info.meanValue = [0.0, 0.0, 0.0]
net1_info.stdValue = 1
net1_info.isOutputYUV = 1
net1_info.isOutputH26X = 0
net1_info.isOutputJPEG = 0
net1_info.imageWidth = cameraCfg.camWidth
net1_info.imageHeight = cameraCfg.camHeight
net1_info.startX = 0
net1_info.startY = 0
net1_info.endX = cameraCfg.camWidth
net1_info.endY = cameraCfg.camHeight
net1_info.inputDimWidth = 300
net1_info.inputDimHeight = 300
# extInputs = np.zeros(ncc.MAX_EXTINPUT_SIZE,dtype = np.uint8)
# print('input size {}'.format(extInputs.size))
net1_info.extInputs = [0] * ncc.MAX_EXTINPUT_SIZE # tobytes()
net1_info.modelCascade = 1
net1_info.inferenceACC = 0
net2_info = ncc.Network2Par()
net2_info.startXAdj = -5
net2_info.startYAdj = -5
net2_info.endXAdj = 5
net2_info.endYAdj = 5
labelMask = [0] * ncc.MAX_LABEL_SIZE
labelMask[1] = 1
net2_info.labelMask = labelMask
net2_info.minConf = 0.7
net2_info.inputDimWidth = 128
net2_info.inputDimHeight = 128
net2_info.inputFormat = ncc.IMG_FORMAT_BGR_PLANAR
net2_info.meanValue = [0.0, 0.0, 0.0]
net2_info.stdValue = 1
count = ncc.MAX_EXTINPUT_SIZE // 2
extInputs = array('h', [0] * count)
net2_info.extInputs = extInputs.tobytes()
net2_info.modelCascade = 0
#print("input 0={} 1={} type={}".format(int(ncc.f32Tof16(1.0)),extInputs[1],type(extInputs[1])));
blob1 = "./blob/2020.3/face-detection-retail-0004/face-detection-retail-0004.blob"
blob2 = "./blob/2020.3/face-reidentification-retail-0095/face-reidentification-retail-0095.blob"
ret = ncc.sdk_net2_init(None, None, \
blob1, net1_info, 0, \
blob2, net2_info, 0)
metasize = 3 * 1024 * 1024
print("xlink_init ret=%d %d" % (ret, metasize))
if (ret < 0):
return
oft_x = net1_info.startX
oft_y = net1_info.startY
dis_w = net1_info.endX - net1_info.startX
dis_h = net1_info.endY - net1_info.startY
offset = struct.calcsize(media_head) # 64
size = cameraCfg.camWidth * cameraCfg.camHeight * 2
yuvbuf = bytearray(size + offset)
metabuf = bytearray(metasize)
ncc.camera_video_out(ncc.YUV420p, ncc.VIDEO_OUT_CONTINUOUS)
bmeta = False
bsave_face = False
if os.access("face.txt", os.F_OK):
faceLib = np.loadtxt('face.txt', dtype=float).tolist()
print(faceLib)
while (True):
size = ncc.GetYuvData(yuvbuf)
if (size <= 0):
time.sleep(0.1) # 0.1 second
continue
numarry = np.array(
yuvbuf[offset:size]) # skip head frameSpecOut 64 bytes
# print("buf len=%d/%d" % (numarry.size,size))
yuv = numarry.reshape(
(int(cameraCfg.camHeight * 3 / 2), cameraCfg.camWidth))
bgr = cv2.cvtColor(yuv, cv2.COLOR_YUV2BGR_I420, 3)
size, outsize0, outsize1, item_num = ncc.GetMetaDataExt(metabuf)
if (size > 0) and (item_num > 0):
bmeta = True
print("ret=%d size0=%d size1=%d,num=%d" %
(size, outsize0, outsize1, item_num))
# spec=metabuf[0:offset]
#type1,seq,m_size=get_header_info(metabuf[0:offset])
#print("meta type=%d seq=%d size=%d" % (type1,seq,m_size))
#f = open("sample.txt", "wb")
#f.write(metabuf)
#f.close()
from_i = offset + ncc.OUTPUT_INDEX_SIZE
count = outsize0 // 2
detMetadata = struct.unpack('H' * count,
metabuf[from_i:from_i + outsize0])
from_i += outsize0 #skip output 0
count = outsize1 // 2
print("out2 count %d from %d to %d" % (count, from_i, size))
secondMeta = struct.unpack('H' * count * item_num,
metabuf[from_i:size])
for i in range(item_num):
image_id = int(ncc.f16Tof32(detMetadata[i * 7 + 0]))
if (image_id < 0):
break
label = int(ncc.f16Tof32(detMetadata[i * 7 + 1]))
score = ncc.f16Tof32(detMetadata[i * 7 + 2])
x0 = ncc.f16Tof32(detMetadata[i * 7 + 3])
y0 = ncc.f16Tof32(detMetadata[i * 7 + 4])
x1 = ncc.f16Tof32(detMetadata[i * 7 + 5])
y1 = ncc.f16Tof32(detMetadata[i * 7 + 6])
# print("item sise=%d score:%.2f<->min:%.2f rec:(%.3f,%.3f)<->(%.3f,%.3f) " %(item_num,score,min_score,x0,y0,x1,y1))
if ((not coordinate_is_valid(x0, y0, x1, y1))
or (score < min_score) or (labelMask[label] == 0)):
continue
x = int(x0 * dis_w + oft_x)
y = int(y0 * dis_h + oft_y)
w = int((x1 - x0) * dis_w)
h = int((y1 - y0) * dis_h)
cv2.rectangle(bgr, (x, y), (x + w, y + h), (255, 128, 128), 2)
regMetadata = secondMeta[i * count:i * count + count]
regRet = array('f')
for j in range(256):
regRet.append(ncc.f16Tof32(regMetadata[j]))
if bsave_face:
print("!!!!save face!!!!")
cv2.imwrite('face.png', bgr)
nf = np.array(regRet)
np.savetxt('face.txt', np.array(nf), fmt='%.2f')
bsave_face = False
similarVal = calc_similar(regRet, faceLib)
result = ''
print("get similar {:.2f}".format(similarVal))
if similarVal > SIMI_VAL:
result = 'RET{:2.2f}, OK'.format(similarVal)
else:
result = 'RET{:2.2f}, NG'.format(similarVal)
cv2.putText(bgr, result, (x, y - 20), cv2.FONT_HERSHEY_COMPLEX,
1, (0, 0, 255), 1)
img_scaled = cv2.resize(bgr,
None,
fx=0.7,
fy=0.7,
interpolation=cv2.INTER_CUBIC)
cv2.namedWindow('openncc', cv2.WINDOW_AUTOSIZE)
cv2.imshow('openncc', img_scaled)
c = cv2.waitKey(10)
if c == 115: #s
bsave_face = True
elif (c == 27):
break
ncc.sdk_uninit()
cv2.destroyAllWindows()