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Added function for choosing data config #2

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Added function for choosing data config #2

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03d9ef2
Added function for choosing data config
Sep 26, 2017
0715d4d
Extended data structure
Sep 26, 2017
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334 changes: 189 additions & 145 deletions o3d3xx/pcic/image_client.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2,152 +2,196 @@
from builtins import *
import struct
import array
import json

from .client import PCICV3Client

class ImageClient(PCICV3Client):
def __init__(self, address, port):
super(ImageClient, self).__init__(address, port)
# disable all result output
self.sendCommand("p0")
# format string for all images
pcicConfig = "{ \"layouter\": \"flexible\", \"format\": { \"dataencoding\": \"ascii\" }, \"elements\": [ { \"type\": \"string\", \"value\": \"star\", \"id\": \"start_string\" }, { \"type\": \"blob\", \"id\": \"normalized_amplitude_image\" }, { \"type\": \"blob\", \"id\": \"distance_image\" }, { \"type\": \"blob\", \"id\": \"x_image\" }, { \"type\": \"blob\", \"id\": \"y_image\" }, { \"type\": \"blob\", \"id\": \"z_image\" }, { \"type\": \"blob\", \"id\": \"confidence_image\" }, { \"type\": \"blob\", \"id\": \"diagnostic_data\" }, { \"type\": \"string\", \"value\": \"stop\", \"id\": \"end_string\" } ] }"
answer = self.sendCommand("c%09d%s" % (len(pcicConfig), pcicConfig))
if str(answer, 'utf-8') != "*":
throw
# enable result output again
self.sendCommand("p1")

def readNextFrame(self):
result = {}

# look for asynchronous output
ticket, answer = self.readNextAnswer()
if ticket == b"0000":
answerIndex = 0

# read start sequence
data = answer[answerIndex:answerIndex+4]
answerIndex += 4
if self.debugFull == True:
print('Read 4 Bytes start sequence: "%s"' % data)

if data != b"star":
print(data)
throw

chunkCounter = 1

while True:
# read next 4 bytes
data = answer[answerIndex:answerIndex+4]
answerIndex += 4

# stop if frame finished
if data == b"stop":
break

# else read rest of image header
data += answer[answerIndex:answerIndex+12]
answerIndex += 12
if self.debugFull == True:
print('Read %d Bytes image header: "%r"' % (len(data), data))

# extract information about chunk
chunkType, chunkSize, headerSize, headerVersion = struct.unpack('IIII', bytes(data))

# read rest of chunk header
data += answer[answerIndex:answerIndex+headerSize-16]
answerIndex += headerSize-16

if headerVersion == 1:
chunkType, chunkSize, headerSize, headerVersion, imageWidth, imageHeight, pixelFormat, timeStamp, frameCount = struct.unpack('IIIIIIIII', bytes(data))
elif headerVersion == 2:
chunkType, chunkSize, headerSize, headerVersion, imageWidth, imageHeight, pixelFormat, timeStamp, frameCount, statusCode, timeStampSec, timeStampNsec = struct.unpack('IIIIIIIIIIII', bytes(data))
else:
print("Unknown chunk header version %d!" % headerVersion)

if self.debug == True:
print('''Data chunk %d:
Chunk type: %d
Chunk size: %d
Header size: %d
Header version: %d
Image width: %d
Image height: %d
Pixel format: %d
Time stamp: %d
Frame counter: %d''' % (chunkCounter, chunkType, chunkSize, headerSize, headerVersion, imageWidth, imageHeight, pixelFormat, timeStamp, frameCount))

# read chunk data
data = answer[answerIndex:answerIndex+chunkSize-headerSize]
answerIndex += chunkSize-headerSize

# distinguish pixel type
if pixelFormat == 0:
image = array.array('B', bytes(data))
elif pixelFormat == 1:
image = array.array('b', bytes(data))
elif pixelFormat == 2:
image = array.array('H', bytes(data))
elif pixelFormat == 3:
image = array.array('h', bytes(data))
elif pixelFormat == 4:
image = array.array('I', bytes(data))
elif pixelFormat == 5:
image = array.array('i', bytes(data))
elif pixelFormat == 6:
image = array.array('f', bytes(data))
elif pixelFormat == 8:
image = array.array('d', bytes(data))
else:
image = None

# distance image
if chunkType == 100:
result['distance'] = image

# amplitude image
elif chunkType == 101:
result['amplitude'] = image

# intensity image
elif chunkType == 102:
result['intensity'] = image

# raw amplitude image
elif chunkType == 103:
result['rawAmplitude'] = image

# X image
elif chunkType == 200:
result['x'] = image

# Y image
elif chunkType == 201:
result['y'] = image

# Z image
elif chunkType == 202:
result['z'] = image

# confidence image
elif chunkType == 300:
result['confidence'] = image

# raw image
elif chunkType == 301:
if 'raw' not in result:
result['raw'] = []
result['raw'].append(image)

# diagnostic data
elif chunkType == 302:
illuTemp, frontendTemp1, frontendTemp2, imx6Temp, evalTime = struct.unpack('=iiiiI', bytes(data))
diagnosticData = dict([('illuTemp', illuTemp/10.0), ('frontendTemp1', frontendTemp1/10.0), ('frontendTemp2', frontendTemp2/10.0), ('imx6Temp', imx6Temp/10.0), ('evalTime', evalTime)])
result['diagnostic'] = diagnosticData

chunkCounter = chunkCounter + 1

# return amplitudeImage, intensityImage, distanceImage, xImage, yImage, zImage, confidenceImage, diagnosticData, rawImage, rawAmplitudeImage
return result

def setDataRequests(self, normAmpl = True, dist=True, x = True, y = True, z = True, conf = True, diag = True, models = True
):
pcicConfig = ("{"
"\"layouter\": \"flexible\","
"\"format\": { \"dataencoding\": \"ascii\" },"
"\"elements\": [")

pcicConfig = pcicConfig + "{ \"type\": \"string\", \"value\": \"star\", \"id\": \"start_string\" },"

if normAmpl is True:
pcicConfig = pcicConfig + "{ \"type\": \"blob\", \"id\": \"normalized_amplitude_image\" },"
if dist is True:
pcicConfig = pcicConfig + "{ \"type\": \"blob\", \"id\": \"distance_image\" },"
if x is True:
pcicConfig = pcicConfig + "{ \"type\": \"blob\", \"id\": \"x_image\" },"
if y is True:
pcicConfig = pcicConfig + "{ \"type\": \"blob\", \"id\": \"y_image\" },"
if z is True:
pcicConfig = pcicConfig + "{ \"type\": \"blob\", \"id\": \"z_image\" },"
if conf is True:
pcicConfig = pcicConfig + "{ \"type\": \"blob\", \"id\": \"confidence_image\" },"
if diag is True:
pcicConfig = pcicConfig + "{ \"type\": \"blob\", \"id\": \"diagnostic_data\" },"
if models is True:
pcicConfig = pcicConfig + "{ \"type\": \"blob\", \"id\": \"json_model\"},"

pcicConfig = pcicConfig + "{ \"type\": \"string\", \"value\": \"stop\", \"id\": \"end_string\" } ] }"

self.sendCommand("p0")
# format string for requesting data
answer = self.sendCommand("c%09d%s" % (len(pcicConfig), pcicConfig))
if str(answer, 'utf-8') != "*":
throw
# enable result output again
self.sendCommand("p1")

def __init__(self, address, port):
super(ImageClient, self).__init__(address, port)
# disable all result output
self.setDataRequests(True, True, True, True, True, True, True)

def readNextFrame(self):
result = {}
# look for asynchronous output
ticket, answer = self.readNextAnswer()
if ticket == b"0000":
answerIndex = 0

# read start sequence
data = answer[answerIndex:answerIndex+4]
answerIndex += 4
if self.debugFull == True:
print('Read 4 Bytes start sequence: "%s"' % data)

if data != b"star":
print(data)
throw

chunkCounter = 1

while True:
# read next 4 bytes
data = answer[answerIndex:answerIndex+4]
answerIndex += 4

# stop if frame finished
if data == b"stop":
break

# else read rest of image header
data += answer[answerIndex:answerIndex+12]
answerIndex += 12
if self.debugFull == True:
print('Read %d Bytes image header: "%r"' % (len(data), data))

# extract information about chunk
chunkType, chunkSize, headerSize, headerVersion = struct.unpack('IIII', bytes(data))

# read rest of chunk header
data += answer[answerIndex:answerIndex+headerSize-16]
answerIndex += headerSize-16

if headerVersion == 1:
chunkType, chunkSize, headerSize, headerVersion, imageWidth, imageHeight, pixelFormat, timeStamp, frameCount = struct.unpack('IIIIIIIII', bytes(data))
elif headerVersion == 2:
chunkType, chunkSize, headerSize, headerVersion, imageWidth, imageHeight, pixelFormat, timeStamp, frameCount, statusCode, timeStampSec, timeStampNsec = struct.unpack('IIIIIIIIIIII', bytes(data))
else:
print("Unknown chunk header version %d!" % headerVersion)

if self.debug == True:
print('''Data chunk %d:
Chunk type: %d
Chunk size: %d
Header size: %d
Header version: %d
Image width: %d
Image height: %d
Pixel format: %d
Time stamp: %d
Frame counter: %d''' % (chunkCounter, chunkType, chunkSize, headerSize, headerVersion, imageWidth, imageHeight, pixelFormat, timeStamp, frameCount))

# read chunk data
data = answer[answerIndex:answerIndex+chunkSize-headerSize]
answerIndex += chunkSize-headerSize

# distinguish pixel type
if pixelFormat == 0:
image = array.array('B', bytes(data))
elif pixelFormat == 1:
image = array.array('b', bytes(data))
elif pixelFormat == 2:
image = array.array('H', bytes(data))
elif pixelFormat == 3:
image = array.array('h', bytes(data))
elif pixelFormat == 4:
image = array.array('I', bytes(data))
elif pixelFormat == 5:
image = array.array('i', bytes(data))
elif pixelFormat == 6:
image = array.array('f', bytes(data))
elif pixelFormat == 8:
image = array.array('d', bytes(data))
else:
image = None

# distance image
if chunkType == 100:
t = 'distance'
result[t] = {'data':image, 'ts': timeStamp, 'resx': imageWidth, 'resy':imageHeight}

# amplitude image
elif chunkType == 101:
t = 'amplitude'
result[t] = {'data':image, 'ts': timeStamp, 'resx': imageWidth, 'resy':imageHeight}

# intensity image
elif chunkType == 102:
t = 'intensity'
result[t] = {'data':image, 'ts': timeStamp, 'resx': imageWidth, 'resy':imageHeight}

# raw amplitude image
elif chunkType == 103:
t = 'rawAmplitude'
result[t] = {'data':image, 'ts': timeStamp, 'resx': imageWidth, 'resy':imageHeight}

# X image
elif chunkType == 200:
t = 'x'
result[t] = {'data':image, 'ts': timeStamp, 'resx': imageWidth, 'resy':imageHeight}

# Y image
elif chunkType == 201:
t = 'y'
result[t] = image
result[t] = {'data':image, 'ts': timeStamp, 'resx': imageWidth, 'resy':imageHeight}

# Z image
elif chunkType == 202:
t = 'z'
result[t] = {'data':image, 'ts': timeStamp, 'resx': imageWidth, 'resy':imageHeight}

# confidence image
elif chunkType == 300:
t = 'confidence'
result[t] = {'data':image, 'ts': timeStamp, 'resx': imageWidth, 'resy':imageHeight}

# raw image
elif chunkType == 301:
t = 'raw'
if t not in result:
result[t] = {'data':[], 'ts': 0, 'resx': 0, 'resy':0}
result[t] = {'data':image, 'ts': timeStamp, 'resx': imageWidth, 'resy':imageHeight}

# diagnostic data
elif chunkType == 302:
illuTemp, frontendTemp1, frontendTemp2, imx6Temp, evalTime = struct.unpack('=iiiiI', bytes(data))
diagnosticData = dict([('illuTemp', illuTemp/10.0), ('frontendTemp1', frontendTemp1/10.0), ('frontendTemp2', frontendTemp2/10.0), ('imx6Temp', imx6Temp/10.0), ('evalTime', evalTime)])
result['diagnostic'] = diagnosticData

elif chunkType == 500:
t = 'models'
result[t] = {'data':data, 'ts': timeStamp}

chunkCounter = chunkCounter + 1

# return amplitudeImage, intensityImage, distanceImage, xImage, yImage, zImage, confidenceImage, diagnosticData, rawImage, rawAmplitudeImage
return result