### Install CLIP-ReID Dependencies with Conda and Pip

Source: https://github.com/syliz517/clip-reid/blob/master/README.md

Installs necessary packages for CLIP-ReID, including PyTorch, torchvision, torchaudio, and several Python libraries like yacs, timm, scikit-image, tqdm, ftfy, and regex, using both conda and pip package managers. Requires Python 3.8 and CUDA toolkit 10.2.

```bash
conda create -n clipreid python=3.8
conda activate clipreid
conda install pytorch==1.8.0 torchvision==0.9.0 torchaudio==0.8.0 cudatoolkit=10.2 -c pytorch
pip install yacs
pip install timm
pip install scikit-image
pip install tqdm
pip install ftfy
pip install regex
```

--------------------------------

### Configure and Train CNN-based CLIP-ReID Baseline

Source: https://github.com/syliz517/clip-reid/blob/master/README.md

Trains a CNN-based CLIP-ReID baseline model on the Market-1501 dataset. Requires modifying the configuration file to specify dataset names and root directory, and setting the output directory. The training is executed using a Python script.

```bash
# Modify configs/person/cnn_base.yml:
# DATASETS:
#    NAMES: ('market1501')
#    ROOT_DIR: ('your_dataset_dir')
# OUTPUT_DIR: 'your_output_dir'

CUDA_VISIBLE_DEVICES=0 python train.py --config_file configs/person/cnn_base.yml
```

--------------------------------

### Train ViT-based CLIP-ReID for MSMT17

Source: https://github.com/syliz517/clip-reid/blob/master/README.md

Trains a ViT-based CLIP-ReID model for the MSMT17 dataset. This involves updating the configuration file with dataset details and output path, then running the training script. Assumes a specific configuration file `vit_clipreid.yml`.

```bash
# Modify configs/person/vit_clipreid.yml:
# DATASETS:
#    NAMES: ('msmt17')
#    ROOT_DIR: ('your_dataset_dir')
# OUTPUT_DIR: 'your_output_dir'

CUDA_VISIBLE_DEVICES=0 python train_clipreid.py --config_file configs/person/vit_clipreid.yml
```

--------------------------------

### Train ViT-based CLIP-ReID with SIE and OLP

Source: https://github.com/syliz517/clip-reid/blob/master/README.md

Trains an advanced ViT-based CLIP-ReID model with SIE (Similarity-aware Instance Embedding) and OLP (Orthogonalized Label Propagation) enhancements for the MSMT17 dataset. This command modifies default configuration parameters for SIE camera, SIE coefficient, and stride size during training.

```bash
CUDA_VISIBLE_DEVICES=0 python train_clipreid.py --config_file configs/person/vit_clipreid.yml MODEL.SIE_CAMERA True MODEL.SIE_COE 1.0 MODEL.STRIDE_SIZE '[12, 12]'
```

--------------------------------

### Evaluate ViT-based CLIP-ReID for MSMT17

Source: https://github.com/syliz517/clip-reid/blob/master/README.md

Evaluates the performance of a trained ViT-based CLIP-ReID model on the MSMT17 dataset. Requires specifying the configuration file and the path to the trained model checkpoints. The evaluation is performed using a dedicated testing script.

```bash
CUDA_VISIBLE_DEVICES=0 python test_clipreid.py --config_file configs/person/vit_clipreid.yml TEST.WEIGHT 'your_trained_checkpoints_path/ViT-B-16_60.pth'
```

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