Image Visualization

Dear ImGui Bundle includes specialized tools for image inspection and debugging.

ImmVision - Image Viewer Widget¶

Introduction¶

ImmVision provides an interactive image viewer widget for ImGui applications, with zoom, pan, pixel inspection, and colormap support. Useful for building image processing tools and debugging computer vision pipelines from within your application.

Quick example:

from imgui_bundle import immvision, immapp
import numpy as np

immvision.use_rgb_color_order()

image = np.zeros((100, 100, 3), dtype=np.uint8)
params = immvision.ImageParams()

def gui():
    # Simple display
    immvision.image_display("Simple", image)

    # Full interactivity (zoom, pan, pixel inspection)
    immvision.image("Interactive", image, params)

immapp.run(gui)

#include "immapp/immapp.h"
#include "immvision/immvision.h"
#include <opencv2/core.hpp>

cv::Mat image;
ImmVision::ImageParams params;

void gui() {
    // Simple display
    ImmVision::ImageDisplay("Simple", image);

    // Full interactivity
    ImmVision::Image("Interactive", image, &params);
}

int main() {
    ImmVision::UseBgrColorOrder();
    image = cv::Mat::zeros(100, 100, CV_8UC3);
    ImmApp::Run(gui);
    return 0;
}

Features:

• Zoom in/out using the mouse wheel

• Pixel values displayed at high zoom levels

• Pan by dragging with left mouse button

• Settings panel for colormap, channels, etc.

Full Demo¶

Documented APIs¶

• Python: immvision.pyi

• C++: image.h | inspector.h

ImmDebug — Standalone Image Debugger¶

Video tutorial on Youtube

ImmDebug a tool from ImmVision lets you visually inspect images from any running program — during execution or even after it finishes (post-mortem). Add one-line calls to send images to a standalone viewer with zoom, pan, pixel inspection, and colormaps.

Python¶

Install from PyPI:

pip install immdebug

Start the viewer in a terminal, then send images from your code:

# In a terminal: immdebug-viewer

import numpy as np
import cv2
from immdebug import immdebug

image = cv2.imread("photo.jpg")
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
edges = cv2.Canny(gray, 100, 200)

immdebug(image, "image")  # inspect the original image
immdebug(gray, "gray")    # inspect different steps of your processing pipeline
immdebug(edges, "edges")  

Works with OpenCV, PIL, matplotlib, or any numpy array. See the immdebug PyPI package for full API documentation.

C++¶

Drop 4 files from src/immdebug into your project (only OpenCV required):

#include "immdebug/immdebug.h"

cv::Mat image = cv::imread("photo.jpg");
ImmVision::ImmDebug(image, "original");

Build and run the C++ viewer separately — see the immvision README for instructions.

Features¶

• Non-blocking — just writes a file and returns immediately

• Cross-language — C++ and Python clients use the same protocol, both work with either viewer

• Post-mortem — images persist in the temp directory for 1 hour; start the viewer after your script finishes

• Single instance — re-launching the viewer brings the existing instance to the top

imgui_tex_inspect - Texture Inspector¶

Introduction¶

imgui_tex_inspect is a texture inspector tool for debugging GPU textures. It displays textures with zoom, pan, and detailed pixel information.

Full Demo¶

• Demo Window | Python | C++

• Simple Example | Python | C++

Documented APIs¶

• Python: imgui_tex_inspect.pyi

• C++: imgui_tex_inspect.h