File size: 704 Bytes
fd2c1e0 1e62ffa fd2c1e0 1e62ffa fd2c1e0 1e62ffa fd2c1e0 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 |
import gradio as gr
import torch
import clip
from PIL import Image
device = "cuda" if torch.cuda.is_available() else "cpu"
model, preprocess = clip.load("ViT-B/32", device=device)
def clip(image, text):
return "UWU"
# image = preprocess(image).unsqueeze(0).to(device)
# text = clip.tokenize([text]).to(device)
# with torch.no_grad():
# image_features = model.encode_image(image)
# text_features = model.encode_text(text)
# logits_per_image, logits_per_text = model(image, text)
# probs = logits_per_image.softmax(dim=-1).cpu().numpy()
# return probs[0]
demo = gr.Interface(fn=clip, inputs=["text", "image"], outputs="text")
demo.launch() |