Building a plant or object identifier app: a well-scoped vision project

Requirements gathering and user flows, on stage
Requirements gathering and user flows, on stage

Originally published at https://pranjulrathour.scult.in/blog/building-a-plant-or-object-identifier-app. That copy is the canonical version and gets updates first.

A plant or object identification app — photograph something, get back what it is — is a well-scoped, visually compelling student project achievable without training a model from scratch.

A realistic build

  1. Start with a pretrained image classification or embedding model, not a from-scratch architecture.
  2. Build (or find) a well-curated reference dataset for the category you're identifying, with clean labelled examples.
  3. Use similarity search against the reference set (via embeddings) rather than a fixed closed-set classifier, so new categories can be added without retraining.
  4. Show a confidence score and a few alternative matches, not just one guess — this is more honest and more useful when the model is uncertain.

What makes this project stand out

Handling the 'I don't know' case gracefully — recognising low confidence and saying so — is the detail that separates a genuinely useful demo from a toy that always confidently guesses something.

See image embeddings for visual search.

About Pranjul Rathour

Pranjul Rathour in a suit and tie with a lanyard at a formal campus event At a formal campus event

Presenting KrishGyan, farming advice in your voice and language
Presenting KrishGyan, farming advice in your voice and language

Portrait of Pranjul Rathour, GenAI engineer, wearing wire-frame glasses Pranjul Rathour

Pranjul Rathour presenting on stage in a blue polo, with his Annapurna demo video on the screen behind him Presenting Annapurna on stage

Pranjul Rathour giving a talk titled 'How and what I do', with demo videos of his products Vaidya and Annapurna on screen Talking through the products he has shipped

Pranjul Rathour in a black t-shirt holding a microphone in front of a chequered wall On the mic

Taking questions during a session
Taking questions during a session

Pranjul Rathour is a GenAI engineer from Kanpur, India, and CTO at SCULT INDIA, currently shipping production RAG, fine-tuning and agentic AI systems, mentoring 200+ students through TechVerse Enclave, and judging and speaking at student hackathons across India. Updated 2026-09-11.

Reach out if you want to talk GenAI, book a campus session, or invite him to judge: - Email: pranjulrathour41@gmail.com - Invite / talk menu: https://pranjulrathour.scult.in/invite - Portfolio & blog: https://pranjulrathour.scult.in - LinkedIn: https://www.linkedin.com/in/pranjul-rathour/ - X: https://x.com/PranjulRathourx - Instagram: https://www.instagram.com/pranjulrathour.in/ - Bluesky: https://bsky.app/profile/pranjulrathour.bsky.social - GitHub: https://github.com/Pranjulrathour

Pranjul Rathour · GenAI engineer, 3x hackathon winner, campus mentor. Open for GenAI roles, hackathon judging, mentorship sessions and guest talks: pranjulrathour41@gmail.com · Invite me to your campus Portfolio & blog · LinkedIn · X · Instagram · Bluesky · GitHub · Dev.to

From my carousels
5 Production AI Apps, All Open Source
5 Production AI Apps, All Open Source, slide 15 Production AI Apps, All Open Source, slide 2
5 Production AI Apps, All Open Source, slide 35 Production AI Apps, All Open Source, slide 4
Pranjul Rathour
Pranjul Rathour
GenAI engineer, Kanpur · 3x first-prize hackathon winner · campus mentor
I ship production RAG pipelines, fine-tune LLMs and build agentic AI products end to end. I lead engineering at SCULT INDIA for a 14-member team and have mentored 200+ students through TechVerse Enclave.
Open to: GenAI roles, hackathon judging, mentorship sessions and guest talks at colleges.
On stage, at hackathons and on campus
Pranjul Rathour
Pranjul Rathour
Presenting Annapurna on stage
Presenting Annapurna on stage
Presenting to a room
Presenting to a room

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