thinc VS clip-as-service

Agree, though I wouldn’t call PyTorch a drop-in for NumPy either. CuPy is the drop-in. Excepting some corner cases, you can use the same code for both. Thinc’s ops work with both NumPy and CuPy:

https://github.com/explosion/thinc/blob/master/thinc/backend...

I love those tiny DNN frameworks, some examples that I studied in the past (I still use PyTorch for work related projects) :

thinc.by the creators of spaCy https://github.com/explosion/thinc

thinc - defining neural nets in functional way jax, a new deep learning framework puts emphasis on functions rather than tensors, I've tested it for a couple of applications and it's really cool, you can write stuff like you'd write math expressions in papers using numpy. That speeds up development significantly, and makes code much more readable

I think training models with limited images can lead to overfitting, so I think you can try using a set of images with different poses. You might also want to try flipping or to help out the model so it gets to do different psoes. You might also want CLIP-as-a-service, but just know that pre-trained models isn't always be the best solution. My .02c

Imagine an AI-powered grep command, one that could process a film and find segments matching a text. With CLIP-as-service, you can do that. Here is the repo link, https://github.com/jina-ai/clip-as-service.

you could try Jina.ai's CLIP-as-a-Service: https://github.com/jina-ai/clip-as-service

Multisearch allows people to search with both text and images. With Open-Source project CLIP-as-service, you can use CLIP (a deep learning model by OpenAI) to do the same. Ask me if you have any questions?

Are you scraping these images or using any dataset? Do share the link, would love to play around with it. Would love to hear your feedback for clip-as-service (what I use in my example)?

Built CLIP-as-service, an open-source library to create embeddings of images and text using CLIP. These embeddings can be used to find the relevant images for any sentence. Note: you don't need to caption the images for this to work, and it is not just limited to objects in the image but an overall understanding built via CLIP neural network.

Built [CLIP-as-service](https://github.com/jina-ai/clip-as-service), an open-source library to create embeddings of images and text using CLIP.

Excited to share my new project CLIP-as-service, a high-scalability service for embedding images and text. It serve CLIP models with ONNX runtime and PyTorch JIT with 800QPS.