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# example python script for capturing an image from Critical Link Camera Platforms
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#
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# conda create -n gentl_38 matplotlib python=3.8
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# conda activate gentl_38
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# pip install numpy harvesters==1.4.0 genicam==1.2.0
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#
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# you must have c:\Program Files\Critical Link LLC\GenTL Viewer\bin in your path prior to running this script.
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# set PATH=c:\Program Files\Critical Link LLC\GenTL Viewer\bin;%PATH%
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#
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# set HARVESTERS_XML_FILE_DIR=C:\Users\jcormier\Documents\Critical Link LLC\gentlviewer\xml
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#
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# To enable simulated camera for testing:
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# copy "c:\Program Files\Critical Link LLC\GenTL Viewer\bin\sim_camera.xml" .
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# set SIMCAM_XML_FILE=sim_camera.xml
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#
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# (gentl_38) C:\Users\jcormier\Documents>python snap.py
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import os
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document_path = os.path.expanduser('~\\Documents')
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os.environ["HARVESTERS_XML_FILE_DIR"] = os.path.join(document_path, "Critical Link LLC\\gentlviewer\\xml")
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print(os.getenv('HARVESTERS_XML_FILE_DIR'))
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print(os.getenv('PATH'))
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from harvesters.core import Harvester
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import logging
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import matplotlib.pyplot as plt
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# set up a logger for the harvester library.
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# this is not needed but can be useful for debugging your script
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logger = logging.getLogger('harvesters');
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ch = logging.StreamHandler()
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logger.setLevel(logging.DEBUG)
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ch.setLevel(logging.DEBUG)
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formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
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ch.setFormatter(formatter)
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logger.addHandler(ch)
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# Create the harvester, don't cleanup downloaded camera xml files
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h = Harvester(logger=logger, do_clean_up=False)
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# the harvester can load dlls as well as cti files.
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if "add_file" in dir(h): # Use updated harvesters api if exists
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h.add_file('c:\\Program Files\\Critical Link LLC\\GenTL Viewer\\bin\\GenTL.dll')
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else:
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h.add_cti_file('c:\\Program Files\\Critical Link LLC\\GenTL Viewer\\bin\\GenTL.dll')
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if "update" in dir(h): # Use updated harvesters api if exists
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h.update()
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else:
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h.update_device_info_list()
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print("Found {} devices".format(len(h.device_info_list)))
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print(h.device_info_list)
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if len(h.device_info_list) == 0:
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print("No devices found")
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exit()
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index = 0
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if len(h.device_info_list) > 1:
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num = None
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while num is None:
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print("More than 1 camera detected,")
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# Print camera name with index
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for idx, dev in enumerate(h.device_info_list):
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print(f"{idx}: {dev.model}")
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num = input("Enter index of camera:")
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try:
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num = int(num)
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except:
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num = None
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index = num
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# create an image acquirer
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if "create" in dir(h): # Use updated harvesters api if exists
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ia = h.create(index)
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else:
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ia = h.create_image_acquirer(list_index=index)
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# this is required for larger images (> 16 MiB) with Critical Link's producer.
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ia.num_buffers = 5
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# Leave default PixelFormat for now
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#ia.remote_device.node_map.PixelFormat.value = 'Mono8'
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# Uncomment to set the image ROI width, height. Otherwise will get full frame
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#ia.remote_device.node_map.Width.value, ia.remote_device.node_map.Height.value = 800, 600
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print("Starting Acquistion")
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if "start" in dir(ia): # Use updated harvesters api if exists
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ia.start()
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else:
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ia.start_image_acquisition()
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# just capture 1 frame
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for i in range(1):
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if "fetch" in dir(ia): # Use updated harvesters api if exists
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fetch = ia.fetch
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else:
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fetch = ia.fetch_buffer
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with fetch(timeout=4) as buffer:
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payload = buffer.payload
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component = payload.components[0]
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width = component.width
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height = component.height
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data_format = component.data_format
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print("Image details: {}w {}h {}".format(width, height, data_format))
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# for monochrome 8 bit images
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if int(component.num_components_per_pixel) == 1:
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content = component.data.reshape(height, width)
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else:
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content = component.data.reshape(height, width, int(component.num_components_per_pixel))
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if int(component.num_components_per_pixel) == 1:
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plt.imshow(content, cmap='gray')
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else:
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plt.imshow(content)
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plt.show()
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#
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if "stop" in dir(ia): # Use updated harvesters api if exists
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ia.stop()
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else:
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ia.stop_image_acquisition()
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ia.destroy()
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