An intelligent system for medicinal plant identification and symptom-based herbal treatment recommendation
Identify a medicinal plant from a photograph, describe how you feel in your own words, and explore the traditional herbal knowledge recorded for the match — with every score explained and every limitation stated.
How a result is produced
- 1
Upload or describe
A leaf photo, a symptom description in your own words, or both together.
- 2
Real inference
The image is classified and your text is scored against the stored herbal records.
- 3
Explained output
Confidence, similarity, matched terms and a Grad-CAM heatmap — plus the precautions that apply.
- 4
Save or print
Keep the analysis in your history or download a print-ready report with the safety notice.
Every figure on screen comes from the analysis service. If a result cannot be produced, the page says so instead of showing an example.
System modules
Four working modules, one integrated flow
Each module maps directly to a block in the approved high-level design, from user input through preprocessing and matching to the final system output.
System modules
Plant Identification
Upload a leaf or plant photo. It is classified by a MobileNetV2 transfer-learning model with 224×224 preprocessing, explained with Grad-CAM.
Open module →Symptom Recommendation
Describe symptoms in plain language and get Top-N herbal information ranked by TF-IDF cosine similarity, with every match explained.
Open module →Combined Analysis
Bring an identified plant and your symptoms together to see how they relate to recorded traditional uses.
Open module →Herbal Knowledge Base
Searchable, filterable plant records: botany, properties, traditional uses, remedies and precautions.
Open module →Target architecture
The interface talks to a single API client, which calls the FastAPI service running the trained image classifier and the fitted symptom matcher over the project's curated datasets.
- Stage 1
User interface
React + TypeScript + Tailwind
- Stage 2
API layer
FastAPI service
- Stage 3
ML & matching
MobileNetV2 · TF-IDF + cosine similarity
- Stage 4
Data & accounts
Curated plant datasets · cloud database