[[Japanese](https://github.com/Kazuhito00/Image-Processing-Node-Editor)/English] > [!IMPORTANT] > This repository is no longer actively maintained. > Core development and major features have been consolidated into **Multimodal-Node-Editor**. > https://github.com/Kazuhito00/Multimodal-Node-Editor # Image-Processing-Node-Editor An application that performs image processing with the node editor.
It is used for processing verification and comparison.

# Note Since the nodes are added in the order in which the author(Takahashi) needs them,
There may be a shortage of nodes responsible for basic processing in image processing.
``` opencv-python 4.5.5.64 or later onnxruntime-gpu 1.12.0 or later dearpygui 1.11.0 or later mediapipe 0.8.10 or later ※Required to run mediapipe node protobuf 3.20.0 or later ※Required to run mediapipe node filterpy 1.4.5 or later ※Required to run MOT(motpy) node ``` # Installation Please prepare the environment by one of the following methods.
* Run the script directly 1. Clone repository
`git clone https://github.com/Kazuhito00/Image-Processing-Node-Editor` 1. Install package
`pip install -r requirements.txt` 1. Run "main.py"
`python main.py` * Use Docker 1. See [Image-Processing-Node-Editor/docker/nvidia-gpu](https://github.com/Kazuhito00/Image-Processing-Node-Editor/tree/main/docker/nvidia-gpu) * Use executable file (Windows only) 1. Download [ipn-editor_win_x86_64.zip](https://github.com/Kazuhito00/Image-Processing-Node-Editor/releases/download/v0.5.0/ipn-editor_v0.5.0_win_x86_64.zip) 1. Run "main.exe" * Use pip installation
※The installed directory names will be "node" and "node_editor", so I plan to fix them in the future.
→When using pip, it is strongly recommended to install in a virtual environment such as venv. 1. Install build tools
Windows：https://visualstudio.microsoft.com/ja/visual-cpp-build-tools/
Ubuntu：`sudo apt-get install build-essential libssl-dev libffi-dev python3-dev` 1. Install Numpy, Cython, wheel
`pip install Cython numpy wheel` 1. Specify the GitHub repository and pip install
`pip install git+https://github.com/Kazuhito00/Image-Processing-Node-Editor` 1. Start the application with the following command
`ipn-editor` # Usage Here's how to run the app. ```bash python main.py ``` * --setting
Specifying the configuration file path that describes the node size and VideoWriter settings
Default：node_editor/setting/setting.json * --unuse_async_draw
Do not use asynchronous drawing
→Perform GUI event loop and node update process in series
*For investigating the cause of abnormal node termination, etc.
Default：unspecified ### Create Node Select the node you want to create from the menu and click

### Connect Node Drag the output terminal to connect to the input terminal
Only the same type set for the terminal can be connected

### Delete Node With the node you want to delete selected, press the "Del" key

### Export Press "Export" from the menu and save the node settings(json file)

### Import Read the node settings(json file) output by Export

# Node

Input Node

Image		Node that reads still images (bmp, jpg, png, gif) and outputs images Open the file dialog with the "Select Image" button
Video		A node that reads a video (mp4, avi) and outputs an image for each frame Open the file dialog with the "Select Movie" button Check "Loop" to play the video in a loop "Skip rate" sets the interval for skipping the output image.
Video(Set Frame Position)		A node that reads a video (mp4, avi) and outputs an image at the specified frame position Open the file dialog with "Select Movie" button
WebCam		A node that reads a webcam and outputs an image for each frame Specify the camera number in the Device No drop-down list
RTSP		A node that reads the RTSP input of a network camera and outputs an image for each frame
Int Value		Node that outputs an integer value
Float Value		Node that outputs the float value

Process Node

ApplyColorMap		A node that applies pseudo color to the input image and outputs a pseudo color image
Blur		A node that executes smoothing processing on the input image and outputs the smoothed image
Brightness		A node that executes brightness adjustment processing on the input image and outputs the brightness adjustment image Brightness adjustment value can be changed with the "alpha" slide bar
Canny		A node that executes edge detection processing using the Canny method on the input image and outputs the edge detection image. Specify the minimum and maximum thresholds with the slider
Contrast		A node that executes contrast adjustment processing on the input image and outputs the contrast adjustment image. Contrast adjustment value can be changed with the "beta" slide bar
Crop		A node that performs cropping of the input image and outputs the cropped image Upper left coordinates(x1, y1) and upper right coordinates(x2, y2) can be changed with the slider
EqualizeHist		Node that performs histogram flattening of the brightness part of the input image and outputs the image
Flip		A node that performs horizontal/vertical inversion to the input image and outputs the image
Gamma Correction		A node that performs gamma correction on the input image and outputs the image Gamma value can be changed with the slider
Grayscale		A node that grayscales the input image and outputs the image
HSV		A node that converts the input image to HSV, manipulates the HSV, and outputs a BGR image
Omnidirectional Viewer		A node that transforms an input image(360-degree image) with the specified roll, pitch, and yaw axes and outputs the image The input image is assumed to be an equirectangular projection image
Resize		A node that resizes the input image with the specified height, width and interpolation method and outputs the image.
Sepia		A node that converts the input image to a sepia image and outputs it
Simple Filter		A node that performs 3x3 2D filtering processing on the input image and outputs the image
Threshold		A node that binarizes the input image and outputs the image Specify the binarization algorithm with "type" Change threshold with "threshold" In "type", "Otsu binarization (THRESH_OTSU)" is an automatic threshold determination algorithm, so the "threshold" value is ignored.

Deep Learning Node

You can specify the model in the drop-down list and change the device at the time of inference with the CPU / GPU checkbox.
* If the model does not support GPU inference, checking GPU will still result in CPU inference
Refer to each directory of "node/deep_learning_node/XXXXXXXX" for the license of the model used by the node.

Classification		Node that performs classification on the input image The output image is a raw image Performs classification on the bounding box when an Object Detection node is connected
Face Detection		Node that performs face detection on the input image The output image is a raw image
Low-Light Image Enhancement		A node that performs Low-Light Image Enhancement on the input image The output image is an image with Low-Light Image Enhancement applied.
Monocular Depth Estimation		A node that performs monocular depth estimation on the input image The output image is a grayscale image to which monocular depth estimation is applied.
Object Detection		Node that performs object detection on the input image The output image is a raw image
Pose Estimation		Node that performs attitude estimation for the input image The output image is a raw image
Semantic Segmentation		Node that performs semantic segmentation on the input image The output image is a raw image
QR Code Detection		Node that executes QR code detection for the input image The output image is a raw image

Analysis Node

FPS		A node that calculates FPS based on the processing time(ms) of the node Processing time input terminal can be added with "Add Slot"
RGB Histgram		Node that calculates the histogram of each RGB channel of the input image and displays it in the graph
BRISQUE		A node that evaluates image quality using BRISQUE * The higher the number, the worse

Draw Node

Draw Information		Draw the analysis result for the image of the node that outputs the raw image such as Classification node and Object Detection node.
Image Concat		Node that displays multiple input images side by side Image input terminal can be added with "Add Slot"
PutText		A node that draws text in the upper left of the input image Drawing color can be selected in the color map By connecting the processing time input terminal, the processing time is also drawn.
Result Image		Node to display the image Display larger than the processing node Also, if you connect a node that outputs raw images such as a Classification node or Object Detection node, the analysis result will be added and drawn.
Result Image(Large)		Larger than the Result Image node

Other Node

ON/OFF Switch		Node to switch whether to output the input image or not
Video Writer		Node to export the input image as a video Output destination, output size, FPS are specified in "setting.json"

Preview Release Node

Nodes whose specifications may change significantly in the future

MOT		Node that inputs an Object Detection node and executes MOT(Multi Object Tracking)
Exec Python Code		Node that executes Python code The variable for the input image is "input_image" The variable for the output image is "output_image"
Screen Capture		Node that captures and outputs the desktop full screen

# Node(Other repository) It is a node published in other repositories.
To use it with Image-Processing-Node-Editor, follow the installation instructions for each repository.

Input Node

YouTube

Node that reads YouTube and outputs images
Please specify the URL of the YouTube video in the URL field and press the "Start" button
It will take some time before playback starts
Specify the YouTube loading interval with "Interval(ms)"

# Json2Deom Experimental tool that generates OpenCV demo code from the Export (JSON) of Image-Processing-Node-Editor. https://github.com/Kazuhito00/ipne-json2demo # ToDo - [ ] Investigating the problem that the graph part of the RGB Histgram node is always in the foreground - [ ] Investigating the problem that the connection line remains when deleting a node that connects multiple nodes - [ ] Improved behavior that the import feature can only be used before adding a node # Author Kazuhito Takahashi(https://twitter.com/KzhtTkhs) # License Image-Processing-Node-Editor is under [Apache-2.0 license](LICENSE).

The source code of Image-Processing-Node-Editor itself is [Apache-2.0 license](LICENSE), but
The source code for each algorithm is subject to its own license.
For details, please check the LICENSE file included in each directory. # License(Image) The images displayed in the sample are borrowed from the [Free Material Pakutaso](https://www.pakutaso.com/),and [NHK Creative Library](https://www.nhk.or.jp/archives).