89 points by codebreaker24 6 months ago flag hide 22 comments
johnsmith 6 months ago next
Great job! I've been looking for a real-time image recognition API and this looks really promising. Do you have any plans for adding video recognition as well?
original_poster 6 months ago next
Hey @johnsmith, thanks for the kind words! Right now, our main focus is on perfecting the image recognition aspect of the API. However, video recognition is definitely something we're keeping in mind for the future. Appreciate your interest and feedback!
janedoe 6 months ago prev next
This is amazing! I'm curious, what technologies did you use to build this API?
original_poster 6 months ago next
@janedoe, we used Python for the API's backend, and TensorFlow for the image recognition model. We also used Flask to build the web server, and Redis for caching. Let me know if you have any other questions!
samantha 6 months ago prev next
Very cool! How did you ensure that the API can handle real-time request?
original_poster 6 months ago next
@samantha, we implemented a load balancer and distributed the requests across multiple servers to ensure that the API can handle real-time requests. We also used a message queue system to process requests as they come in. Would you like to hear more details about it?
kevin 6 months ago prev next
This is really impressive. I'm planning to build something similar, any tips you could share for getting started?
original_poster 6 months ago next
@kevin, thank you! A few tips I would give for getting started are to first decide on the technologies and infrastructure you want to use, then design and train your model, and finally build the API and test it thoroughly. Don't be afraid to ask for help if you get stuck, and remember to keep a strong focus on security and data privacy.
tom 6 months ago prev next
I love how you open sourced the code. Kudos to you! :thumbsup:
original_poster 6 months ago next
@tom, thank you! We believe in the power of open source, and hope that others will find our work useful for their own projects.
steve 6 months ago prev next
Have you considered using a cloud provider for deployment? It could help with scalability and cost.
original_poster 6 months ago next
@steve, thank you for the suggestion. We have considered using a cloud provider, and it's definitely something we may explore in the future to help with scalability and cost. However, for now, we're happy with our current setup.
jeff 6 months ago prev next
Have you thought about monetizing this? It seems like it could be a valuable service for businesses and individuals alike.
original_poster 6 months ago next
@jeff, thank you for the suggestion. Right now, our main focus is on improving the API and getting it ready for production use. However, monetizing the service is definitely something we've considered, and will likely explore in the future.
alice 6 months ago prev next
The real-time aspect of the API is really impressive. Have you considered integrating it with real-time communication platforms?
original_poster 6 months ago next
@alice, thank you! Integrating the real-time image recognition with real-time communication platforms is definitely something we've thought about, and would love to explore in the future. Let us know if you have any specific use cases in mind.
bob 6 months ago prev next
This is amazing! I can't wait to see where you take this.
original_poster 6 months ago next
@bob, thank you! We're excited about the potential of the API as well, and are working hard to bring it to its full potential. Appreciate your support!
ben 6 months ago prev next
Agreed, this is very cool. How long did it take you to build the API?
original_poster 6 months ago next
@ben, thank you! The development of the API took a few months, but of course, a significant amount of time was spent on researching, planning, and testing as well.
carol 6 months ago prev next
Yeah, can you share more about the research and planning phase? I'm always curious about that part of projects.
original_poster 6 months ago next
@carol, of course! For the research phase, we looked into existing image recognition technologies and compared their features, strengths and weaknesses. We also studied best practices for building APIs and consulted relevant literature and documentation. For the planning phase, we then designed the overall architecture, established milestones, and allocated resources. We also spent time testing different approaches before choosing the final one.