Update README.md

README.md

@@ -9,10 +9,6 @@ tags:
 - basnet
 ---
 
-# PosterO Saliency Detection Models
-
-This repository contains the saliency detection model weights for the PosterO evaluation pipeline.
-
 ## Models Included
 
 ### ISNet (isnet-general-use.pth)
@@ -27,64 +23,4 @@ This repository contains the saliency detection model weights for the PosterO ev
 - **Input Size**: 256×256
 - **Usage**: Secondary saliency map generation
 
-## Usage
-
-These models are automatically downloaded and used by the PosterO evaluation script:
-
-```bash
-# Basic usage - models download automatically
-python run_saliency_and_eval_hf.py \
-    --input_dir ./images \
-    --predictions ./predictions.json \
-    --output_dir ./results
-
-# Or specify the repository explicitly
-python run_saliency_and_eval_hf.py \
-    --input_dir ./images \
-    --predictions ./predictions.json \
-    --output_dir ./results \
-    --hf_isnet_repo "pengdaica/saliency_weights" \
-    --hf_basnet_repo "pengdaica/saliency_weights"
-```
-
-## Evaluation Pipeline
-
-The final saliency map used in evaluation is computed as the **element-wise maximum** of both models:
-
-```python
-final_saliency = np.maximum(isnet_map, basnet_map)
-```
-
-This approach leverages the strengths of both architectures:
-- ISNet provides high-resolution, detailed saliency detection
-- BASNet offers complementary detection patterns
-- Maximum operation captures the union of salient regions
-
-## Model Details
-
-| Model | File | Size | Resolution | Framework |
-|-------|------|------|------------|-----------|
-| ISNet | `isnet-general-use.pth` | ~168 MB | 1024×1024 | PyTorch |
-| BASNet | `gdi-basnet.pth` | ~332 MB | 256×256 | PyTorch |
-
-## Installation
-
-```bash
-pip install torch torchvision huggingface_hub pillow opencv-python numpy matplotlib cairosvg tqdm
-```
-
-## Citation
-
-If you use these models, please cite the original PosterO paper and the respective saliency detection methods:
-
-- ISNet: [Intermediate Supervision Network for Salient Object Detection](https://arxiv.org/abs/2109.12172)
-- BASNet: [Boundary-Aware Segmentation Network for Mobile and Web Applications](https://arxiv.org/abs/2101.04704)
-
-## License
-
-Apache 2.0
-
-## Repository
 
-- **Code**: [PosterO-CVPR2025](https://github.com/your-repo/PosterO-CVPR2025)
-- **Models**: [pengdaica/saliency_weights](https://huggingface.co/pengdaica/saliency_weights)