Control Camera in BB

In this tutorial, we learn how to set Gain and Exposure time manually on ion-kit based on the previous tutorial that display 1-camera image, and display multiple cameras images

To control Gain and ExposureTime without BB, you may want to see Access and Set Device Info or arv-tool-0.8.

Prerequisite

• ionpy
• numpy
• OpenCV

pip3 install -U pip
pip3 install opencv-python
pip3 install numpy
pip3 install ion-python==1.8.10

Tutorial

Get Device Information

To display images with ionpy, we need to get the following information of the device.

• Width
• Height
• PixelFormat

The previous tutorial or arv-tool-0.8 will help to get these values.

Build a pipeline

While the structurte of BB is the same as the tutorial that display 1-camera image, and tutorial that display multiple cameras image, we need some small changes to enable Gain and ExposureTime setting.

In this tutorial, we can set Gain and ExposureTime manually by setting enable_control to true.

While port input is dynamic; i.e. it can be updated for each run, you can set static values in string via Param. For example, the value of Gain and ExposureTime is set by port to update in each run, and the key of these values are static, so whould be set by Param as follows:

# set params
enable_control = Param('enable_control', 'true')
gain_key = Param('gain_key', 'Gain')
exposure_key = Param('exposure_key', 'ExposureTime')

# set ports
gain_ps = []
exposure_ps = []
for i in range(num_device):
    gain_ps.append(Port('gain' + str(i), Type(TypeCode.Float, 64, 1), 0))
    exposure_ps.append(Port('exposure' + str(i), Type(TypeCode.Float, 64, 1), 0))

gain_values = []
exposure_values = []

for i in range(num_device):
    gain_values.append(40.0)
    exposure_values.append(100.0)

# add enable_control
node = builder.add(bb_name)\
        .set_iport([gain_ps[0], exposure_ps[0]])\
        .set_param([num_devices, frame_sync, realtime_display_mode, enable_control, gain_key, exposure_key]) if num_device == 1 \
        else builder.add(bb_name)\
            .set_iport([gain_ps[0], exposure_ps[0], gain_ps[1], exposure_ps[1]])\
            .set_param([num_devices, frame_sync, realtime_display_mode, enable_control, gain_key, exposure_key])

Then, bind the input values to ports. This is similar to bind the output ports and output buffers.

# bind gain values and exposuretime vlaues
for i in range(num_device):
    gain_ps[i].bind(gain_values[i])
    exposure_ps[i].bind(exposure_values[i])

Now, we have set Gain and ExposureTime successfully!

why it does not work

gain_key and exposure_key are the feature key of GenICam to control device gain and exposure time. With SFNC (Standard Features Naming Convention) by emva; they are usually set Gain and ExposureTime; however, some device has different key.

In that case, you may need to change the name of the keys of param. This page to check how to list the available features.

gain_key = Param('gain_key', <name of the feature to control gain>)
exposure_key = Param('exposure_key', <name of the feature to control exposure time>)

Execute the pipeline

Execute builder.run() to finish the pipeline.

Update the input port values in each run

In the previous tutorials, we have just displayed the output image in each run. This time, you can update the value of Gain or ExposureTime. The following example shows how to increase Gain by 1.0 for every run bi updating gain_values and re-bind the updates.

while(user_input == -1):
    gain_values[0] += 1.0
    gain_ps[0].bind(gain_values[0])

    # running the builder
    builder.run()
    for i in range(num_device):
        output_datas[i] *= coef
        cv2.imshow("img" + str(i), output_datas[i])
    user_input = cv2.waitKeyEx(1)

Do not forget to destroy windows that displayed the image after for loop.

cv2.destroyAllWindows()

Complete code

Complete code used in the tutorial is here.