Muhammad8815/inno-rmbg-removal-8815
By Muhammad8815 · ↓ 0 · ♥ 0 · Updated 2025-08-04
What's in this repo
This page lists the files in Muhammad8815/inno-rmbg-removal-8815, including model.onnx, model_fp16.onnx, model_quantized.onnx.
- 3 ONNX models (.onnx files)
- 21 files, including 6 .py, 3 .json, 3 .onnx, 2 .png, 1 .md, 1 .jpg
- Last updated 2025-08-04
ONNX files
| File | Size | Download |
|---|---|---|
| onnx/model.onnx | — | Download |
| onnx/model_fp16.onnx | — | Download |
| onnx/model_quantized.onnx | — | Download |
How to use
These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.
README
title: Inno Background Remover emoji: 🪄 colorFrom: pink colorTo: purple sdk: gradio sdk_version: "4.19.2" app_file: app.py pinned: false
🪄 Inno RMBG Removal v1.0
This Space runs a custom-trained image background removal model using PyTorch and ONNX.
It performs pixel-wise background removal on input images with high accuracy using a Gradio interface.
✨ Model Highlights
- Trained on diverse images of objects, people, and scenes.
- Outputs a binary mask of the foreground.
- Works with
.pthand ONNX formats. - Useful for background replacement or transparent cutouts.
📦 Input / Output
Input Image:
Output (no background):
🧪 How It Works
- Upload an image using the UI.
- The model generates a mask for the foreground.
- The output is a transparent PNG or white background version.
⚙️ Inference Code (example)
from PIL import Image
from utilities import preprocess_image, postprocess_image, load_model
model = load_model("model.pth")
image = Image.open("example_input.jpg")
mask = model.predict(image)
image.putalpha(mask)
image.save("output.png")
Model info
Created: 2025-07-28
Updated: 2025-08-04
View on Hugging FaceFiles (21)
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