Showing 4 open source projects for "cpu-x"

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  • 1
    Lama Cleaner

    Lama Cleaner

    Image inpainting tool powered by SOTA AI Model

    ...You can use it to remove any unwanted object, defect, or people from your pictures or erase and replace anything on your pictures. Many AICG creators are using Lama Cleaner to clean-up their work. Completely free and open-source, fully self-hosted, supports CPU & GPU. Windows 1-Click Installer, classical image inpainting algorithm powered by cv2. Multiple SOTA AI models, and various inpainting strategies. Run as a desktop application. Interactive Segmentation on any object.
    Downloads: 66 This Week
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  • 2
    IOPaint

    IOPaint

    Image inpainting tool powered by SOTA AI Model

    IOPaint is a powerful open-source image editing tool focused on inpainting, outpainting, object removal, and general image manipulation driven by state-of-the-art AI models, delivering these capabilities through both local and hosted workflows. Designed to be fully self-hosted and flexible, IOPaint supports a variety of underlying generators and inpaint models — from LaMa erase networks to Stable Diffusion-based replace/object generation — giving users multiple ways to refine or reconstruct...
    Downloads: 12 This Week
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  • 3
    DALL-E 2 - Pytorch

    DALL-E 2 - Pytorch

    Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis

    ...Specifically, this repository will only build out the diffusion prior network, as it is the best performing variant (but which incidentally involves a causal transformer as the denoising network) To train DALLE-2 is a 3 step process, with the training of CLIP being the most important. To train CLIP, you can either use x-clip package, or join the LAION discord, where a lot of replication efforts are already underway. Then, you will need to train the decoder, which learns to generate images based on the image embedding coming from the trained CLIP.
    Downloads: 1 This Week
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  • 4
    Stable Diffusion in Docker

    Stable Diffusion in Docker

    Run the Stable Diffusion releases in a Docker container

    ...On less powerful GPUs you may need to modify some of the options; see the Examples section for more details. If you lack a suitable GPU you can set the options --device cpu and --onnx instead. Since it uses the model, you will need to create a user access token in your Huggingface account. Save the user access token in a file called token.txt and make sure it is available when building the container. Create an image from an existing image and a text prompt. Modify an existing image with its depth map and a text prompt.
    Downloads: 0 This Week
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