This is the Linux app named CLIP whose latest release can be downloaded as CLIPsourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
Download and run online this app named CLIP with OnWorks for free.
Follow these instructions in order to run this app:
- 1. Downloaded this application in your PC.
- 2. Enter in our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.
- 3. Upload this application in such filemanager.
- 4. Start the OnWorks Linux online or Windows online emulator or MACOS online emulator from this website.
- 5. From the OnWorks Linux OS you have just started, goto our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.
- 6. Download the application, install it and run it.
SCREENSHOTS
Ad
CLIP
DESCRIPTION
CLIP (Contrastive Language-Image Pretraining) is a neural model that links images and text in a shared embedding space, allowing zero-shot image classification, similarity search, and multimodal alignment. It was trained on large sets of (image, caption) pairs using a contrastive objective: images and their matching text are pulled together in embedding space, while mismatches are pushed apart. Once trained, you can give it any text labels and ask it to pick which label best matches a given image—even without explicit training for that classification task. The repository provides code for model architecture, preprocessing transforms, evaluation pipelines, and example inference scripts. Because it generalizes to arbitrary labels via text prompts, CLIP is a powerful tool for tasks that involve interpreting images in terms of descriptive language.
Features
- Shared embedding space for images and text enabling zero-shot classification
- Model code for architecture, preprocessing, training, and inference
- Support for custom prompt templates and label embeddings
- Image/text similarity scoring and retrieval pipelines
- Example usage scripts and evaluation benchmarks
- Adaptation to new data or labels without retraining via prompt methods
Programming Language
Python
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/clip.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.