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license: mit |
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--- |
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### Simple running code is based on [CoLLaVO-Github](https://github.com/ByungKwanLee/CoLLaVO). |
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You need only the following seven steps. |
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### [0] Download Github Code of CoLLaVO, install the required libraries, set the necessary environment variable (README.md explains in detail! Don't Worry!). |
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```bash |
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git clone https://github.com/ByungKwanLee/CoLLaVO |
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bash install |
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``` |
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### [1] Loading Image |
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```python |
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from PIL import Image |
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from torchvision.transforms import Resize |
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from torchvision.transforms.functional import pil_to_tensor |
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image_path = "figures/crayon_image.jpg" |
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image = Resize(size=(490, 490), antialias=False)(pil_to_tensor(Image.open(image_path))) |
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``` |
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### [2] Instruction Prompt |
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```python |
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prompt = "Describe this image in detail." |
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``` |
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### [3] Loading CoLlaVO |
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```python |
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from collavo.load_collavo import prepare_collavo |
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collavo_model, collavo_processor, seg_model, seg_processor = prepare_collavo(collavo_path='BK-Lee/CoLLaVO-7B', bits=4, dtype='fp16') |
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``` |
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### [4] Pre-processing for CoLLaVO |
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```python |
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collavo_inputs = collavo_model.demo_process(image=image, |
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prompt=prompt, |
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processor=collavo_processor, |
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seg_model=seg_model, |
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seg_processor=seg_processor, |
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device='cuda:0') |
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``` |
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### [5] Generate |
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```python |
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import torch |
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with torch.inference_mode(): |
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generate_ids = collavo_model.generate(**collavo_inputs, do_sample=True, temperature=0.9, top_p=0.95, max_new_tokens=256, use_cache=True) |
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``` |
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### [6] Decoding |
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```python |
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answer = collavo_processor.batch_decode(generate_ids, skip_special_tokens=True)[0].split('[U')[0] |
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print(answer) |
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``` |
