https://github.com/nikhilroxtomar/multiclass-segmentation-on-crowd-instance-level-human-parsing-chip-dataset-using-unet
Multiclass Segmentation using UNET on Crowd Instance-level Human Parsing (CHIP) dataset
https://github.com/nikhilroxtomar/multiclass-segmentation-on-crowd-instance-level-human-parsing-chip-dataset-using-unet
chip-dataset multiclass-segmentation unet
Last synced: 5 months ago
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Multiclass Segmentation using UNET on Crowd Instance-level Human Parsing (CHIP) dataset
- Host: GitHub
- URL: https://github.com/nikhilroxtomar/multiclass-segmentation-on-crowd-instance-level-human-parsing-chip-dataset-using-unet
- Owner: nikhilroxtomar
- Created: 2022-10-28T12:32:09.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2022-10-28T15:45:56.000Z (over 2 years ago)
- Last Synced: 2024-11-16T06:28:09.399Z (7 months ago)
- Topics: chip-dataset, multiclass-segmentation, unet
- Language: Python
- Homepage:
- Size: 16.3 MB
- Stars: 11
- Watchers: 3
- Forks: 3
- Open Issues: 2
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Metadata Files:
- Readme: README.md
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README
# Multiclass Segmentation on Crowd Instance-level Human Parsing (CHIP) Dataset using UNET
This repository contains the code for the Multiclass Segmentation using the UNET architecture on the Crowd Instance-level Human Parsing (CHIP) Dataset. The complete code is written using the TensorFlow frameowork.
## Dataset
Download the dataset: [Crowd Instance-level Human Parsing (CHIP)](https://drive.google.com/uc?id=1B9A9UCJYMwTL4oBEo4RZfbMZMaZhKJaz)
## Results
The sequence of the images are: 1) Input Image 2) Ground Truth Mask and 3) Prediction Mask
## Contact:
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