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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() |