FrameGrab is an open-source Python library designed to make it easy to grab frames (images) from cameras or streams. The library supports generic USB cameras (such as webcams), RTSP streams, Basler USB cameras, Basler GigE cameras, and Intel RealSense depth cameras.
FrameGrab also provides basic motion detection functionality. FrameGrab requires Python 3.7 or higher.
To install the FrameGrab library, simply run:
pip install framegrab
Certain camera types have additional dependencies that must be installed separately. If you don't intend to use these camera types, you don't need to install these extra packages.
- To use a Basler USB or GigE camera, you must separately install the
pypylon
package. - To use Intel RealSense cameras, you must install
pyrealsense2
. - To use a Raspberry Pi "CSI2" camera (connected with a ribbon cable), you must install the
picamera2
library. See install instructions at the picamera2 github repository.
There is a simple CLI for framegrab
to discover and preview configurations.
framegrab
lists the sub-commands, including autodiscover
and preview
.
Frame Grabbers are defined by a configuration dict which is usually stored as YAML. The configuration combines the camera type, the camera ID, and the camera options. The configuration is passed to the FrameGrabber.create_grabber
method to create a grabber object. The grabber object can then be used to grab frames from the camera.
config
can contain many details and settings about your camera, but only input_type
is required. Available input_type
options are: generic_usb
, rtsp
, realsense
, basler
, and rpi_csi2
.
Here's an example of a single USB camera configured with several options:
config = """
name: Raspberry Pi Ribbon Cable Camera
input_type: rpi_csi2
options:
resolution:
height: 720
width: 1280
zoom:
digital: 1.5
"""
grabber = FrameGrabber.create_grabber_yaml(config)
To get a frame, simply run:
frame = grabber.grab()
You can also change the options after the grabber is created.
new_options = {
'resolution': {
'height': 480,
'width': 640,
},
'crop': {
'relative': {
'top': .1,
'bottom': .9,
'left': .1,
'right': .9,
}
}
}
grabber.apply_options(new_options)
When you are done with the camera, release the resource by running:
grabber.release()
You might have several cameras that you want to use in the same application. In this case, you can load the configurations from a yaml file and use FrameGrabber.create_grabbers
. Note that currently only a single Raspberry Pi CSI2 camera is supported, but these cameras can be used in conjunction with other types of cameras.
If you have multiple cameras of the same type plugged in, it's recommended that you include serial numbers in the configurations; this ensures that each configuration is paired with the correct camera. If you don't provide serial numbers in your configurations, configurations will be paired with cameras in a sequential manner.
Below is a sample yaml file containing configurations for three different cameras.
image_sources:
- name: On Robot Arm
input_type: basler
id:
serial_number: A24P1V4T
options:
crop:
relative:
top: 0.3
right: 0.8
- name: Chip Bin
input_type: rtsp
id:
rtsp_url: rtsp://admin:password@192.168.1.20/cam/realmonitor?channel=1&subtype=0
options:
crop:
pixels:
top: 350
bottom: 1100
left: 1100
right: 2000
- name: Over CNC Machine
input_type: generic_usb
id:
serial_number: B77D3A8F
You can load the configurations from the yaml file and use the cameras in the following manner.
from framegrab import FrameGrabber
config_path = 'camera_config.yaml'
grabbers = FrameGrabber.from_yaml(config_path)
for grabber in grabbers.values():
print(grabber.config)
frame = grabber.grab()
display_image(frame) # substitute this line for your preferred method of displaying images, such as cv2.imshow
grabber.release()
The table below shows all available configurations and the cameras to which they apply.
Configuration Name | Example | Generic USB | RTSP | Basler | Realsense | Raspberry Pi CSI2 |
---|---|---|---|---|---|---|
name | On Robot Arm | optional | optional | optional | optional | optional |
input_type | generic_usb | required | required | required | required | required |
id.serial_number | 23458234 | optional | - | optional | optional | - |
id.rtsp_url | rtsp://… | - | required | - | - | - |
options.resolution.height | 480 | optional | - | - | optional | - |
options.resolution.width | 640 | optional | - | - | optional | - |
options.zoom.digital | 1.3 | optional | optional | optional | optional | optional |
options.crop.pixels.top | 100 | optional | optional | optional | optional | optional |
options.crop.pixels.bottom | 400 | optional | optional | optional | optional | optional |
options.crop.pixels.left | 100 | optional | optional | optional | optional | optional |
options.crop.pixels.right | 400 | optional | optional | optional | optional | optional |
options.crop.relative.top | 0.1 | optional | optional | optional | optional | optional |
options.crop.relative.bottom | 0.9 | optional | optional | optional | optional | optional |
options.crop.relative.left | 0.1 | optional | optional | optional | optional | optional |
options.crop.relative.right | 0.9 | optional | optional | optional | optional | optional |
options.depth.side_by_side | 1 | - | - | - | optional | - |
options.num_90_deg_rotations | 2 | optional | optional | optional | optional | optional |
options.keep_connection_open | True | - | optional | - | - | - |
options.max_fps | 30 | - | optional | - | - | - |
In addition to the configurations in the table above, you can set any Basler camera property by including options.basler.<BASLER PROPERTY NAME>
. For example, it's common to set options.basler.PixelFormat
to RGB8
.
Autodiscovery automatically connects to cameras that are plugged into your machine or discoverable on the network, including generic_usb
, realsense
, basler
, and ONVIF supported rtsp
cameras. Note that rpi_csi2
cameras are not yet supported by autodiscover. Default configurations will be loaded for each camera. Note that discovery of RTSP cameras will be disabled by default but can be enabled by setting rtsp_discover_mode
. Refer to RTSP Discovery section for different options.
Autodiscovery is great for simple applications where you don't need to set any special options on your cameras. It's also a convenient method for finding the serial numbers of your cameras (if the serial number isn't printed on the camera).
grabbers = FrameGrabber.autodiscover()
# Print some information about the discovered cameras
for grabber in grabbers.values():
print(grabber.config)
grabber.release()
RTSP cameras with support for ONVIF can be discovered on your local network in the following way:
from framegrab import RTSPDiscovery, ONVIFDeviceInfo
devices = RTSPDiscovery.discover_onvif_devices()
The discover_onvif_devices()
will provide a list of devices that it finds in the ONVIFDeviceInfo
format. An optional mode auto_discover_mode
can be used to try different default credentials to fetch RTSP URLs:
- off: No discovery.
- ip_only: Only discover the IP address of the camera.
- light: Only try first two usernames and passwords ("admin:admin" and no username/password).
- complete_fast: Try the entire DEFAULT_CREDENTIALS without delays in between.
- complete_slow: Try the entire DEFAULT_CREDENTIALS with a delay of 1 seconds in between.
After getting the list and enter the username and password of the camera. Use generate_rtsp_urls()
to generate RTSP URLs for each devices.
for device in devices:
RTSPDiscovery.generate_rtsp_urls(device=device)
This will generate all the available RTSP URLs and can be used when creating FrameGrabber.create_grabbers
to grab frames.
config = f"""
name: Front Door Camera
input_type: rtsp
id:
rtsp_url: {device.rtsp_urls[0]}
"""
grabber = FrameGrabber.create_grabber_yaml(config)
To use the built-in motion detection functionality, first create a MotionDetector
object, specifying the percentage threshold for motion detection:
from framegrab import MotionDetector
motion_threshold = 1.0
m = MotionDetector(pct_threshold=motion_threshold)
The motion threshold is defined as the detection threshold for motion detection, in terms of the percentage of changed pixels. The default value is 1.0 (which means 1%).
Then, use the motion_detected()
method with a captured frame to check if motion has been detected:
if m.motion_detected(frame):
print("Motion detected!")
Here's an example of using the FrameGrab library to continuously capture frames and detect motion from a video stream:
from framegrab import FrameGrabber, MotionDetector
motion_threshold = 1.0
config = {
'input_type': 'generic_usb',
}
grabber = FrameGrabber.create_grabber(config)
m = MotionDetector(pct_threshold=motion_threshold)
while True:
frame = grabber.grab()
if frame is None:
print("No frame captured!")
continue
if m.motion_detected(frame):
print("Motion detected!")
We welcome contributions to FrameGrab! If you would like to contribute, please follow these steps:
- Fork the repository
- Create a new branch for your changes
- Commit your changes to the branch
- Open a pull request
FrameGrab is released under the MIT License. For more information, please refer to the LICENSE.txt file.