image = transform(Image.open("image.jpg")).unsqueeze(0).to(device) text_inputs = torch.tensor(["a photo of a cat", "a picture of a dog"]).to(device) # Get image and text features image_features = model.encode_image(image) text_features = model.encode_text(text_inputs) CLIP 结...
from langchain.llms import Replicate text2image = Replicate( model="stability-ai/stable-diffusion:db21e45d3f7023abc2a46ee38a23973f6dce16bb082a930b0c49861f96d1e5bf", input={"image_dimensions": "512x512"}, ) image_url = text2image("a book cover for a book about creating generative ai ...
device="cuda"iftorch.cuda.is_available()else"cpu"model,transform=clip.load("ViT-B/32",device)# Prepare image and text inputs image=transform(Image.open("image.jpg")).unsqueeze(0).to(device)text_inputs=torch.tensor(["a photo of a cat","a picture of a dog"]).to(device)# Get ima...
Eye for AI Easy Text-to-Image Tools and Templates. Create images from text in under a minute. ✅ Facet 2.0 Facet: Image Creation, Reimagined. Harness the power of AI to make the creative process fast, effective and accessible. Experiment with visual directions, automate selections, and colla...
muse is a fast, state-of-the-art text-to-image generation and editing model. ✅ Human Generator Create hyperrealistic full-body photos of people in real-time Created from scratch by AI, Generated Photos are perfect for ads, design, marketing, research, and machine learning ✅ Weshop Wes...
Attributes Extractor 2.4. Generator 2.5. Postprocessing 2.6. Evaluation Methods 3. Challenges 4. Conclusions 5. Future Directions 0、前言 第 11 页 /共 36 页 【GigaGAN论文总结】Scaling up GANs for Text- to-Image Synthesis 【GigaGAN论文总结】Scaling up GANs for Text-to-Image Synthesis 1、论点...
from towhee.models.visualization.clip_visualizationimportshow_attention_for_clip from towhee.models.clipimportclip cat_dog_img=Image.open('cat_and_dog.png')model=clip.create_model(model_name="clip_vit_b32",pretrained=True,device="cpu",jit=False,vis=True)text_list=['a dog','a cat','The ...
echo"生成字符集"unicharset_extractor tg.font.exp0.box mftraining-Ffont_properties-Uunicharset-Otg.unicharset tg.font.exp0.tr echo"聚类"cntraining tg.font.exp0.tr echo"重命名"cp normproto tg.normproto cp inttemp tg.inttemp cp pffmtable tg.pffmtable ...
Text Encoder：Transformer模型 Image Encoder：ViT模型 两组输出计算余弦相似度，采用交叉熵损失进行训练。
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