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Build error
| import os | |
| import sys | |
| os.system("git clone https://github.com/salesforce/BLIP") | |
| sys.path.append("BLIP") | |
| os.chdir("BLIP") | |
| os.system("wget https://upload.wikimedia.org/wikipedia/commons/thumb/e/ec/Mona_Lisa%2C_by_Leonardo_da_Vinci%2C_from_C2RMF_retouched.jpg/1024px-Mona_Lisa%2C_by_Leonardo_da_Vinci%2C_from_C2RMF_retouched.jpg -O mona.jpg") | |
| from PIL import Image | |
| import requests | |
| import torch | |
| from torchvision import transforms | |
| from torchvision.transforms.functional import InterpolationMode | |
| device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') | |
| import gradio as gr | |
| from models.blip import blip_decoder | |
| image_size = 384 | |
| transform = transforms.Compose([ | |
| transforms.Resize((image_size,image_size),interpolation=InterpolationMode.BICUBIC), | |
| transforms.ToTensor(), | |
| transforms.Normalize((0.48145466, 0.4578275, 0.40821073), (0.26862954, 0.26130258, 0.27577711)) | |
| ]) | |
| model_url = 'https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model*_base_caption.pth' | |
| model = blip_decoder(pretrained=model_url, image_size=384, vit='base') | |
| model.eval() | |
| model = model.to(device) | |
| def inference(raw_image): | |
| image = transform(raw_image).unsqueeze(0).to(device) | |
| with torch.no_grad(): | |
| caption = model.generate(image, sample=False, num_beams=3, max_length=20, min_length=5) | |
| print('caption: '+caption[0]) | |
| return 'caption: '+caption[0] | |
| inputs = gr.inputs.Image(type='pil') | |
| outputs = gr.outputs.Textbox(label="Output") | |
| title = "Omnivore" | |
| description = "Gradio demo for Omnivore: A Single Model for Many Visual Modalities. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below." | |
| article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2201.08377' target='_blank'>Omnivore: A Single Model for Many Visual Modalities</a> | <a href='https://github.com/facebookresearch/omnivore' target='_blank'>Github Repo</a></p>" | |
| gr.Interface(inference, inputs, outputs, title=title, description=description, article=article, examples=[['mona.jpg']]).launch(enable_queue=True,cache_examples=True) |