| import gradio as gr | |
| import open_clip | |
| import torch | |
| device = torch.device("cuda" if torch.cuda.is_available() else "cpu") | |
| model, _, transform = open_clip.create_model_and_transforms( | |
| "coca_ViT-L-14", | |
| pretrained="mscoco_finetuned_laion2B-s13B-b90k" | |
| ) | |
| model.to(device) | |
| def output_generate(image): | |
| im = transform(image).unsqueeze(0).to(device) | |
| generated = model.generate(im, seq_len=20) | |
| return open_clip.decode(generated[0].detach()).split("<end_of_text>")[0].replace("<start_of_text>", "") | |
| iface = gr.Interface(fn=output_generate, inputs=gr.Image(type="pil"), outputs="text") | |
| iface.launch() |