leaf-diseases-detect and Corn-Leaf-Diseases-Detection
These are competitors—both are end-to-end Streamlit applications for leaf disease detection, but A uses a vision LLM (Llama Vision via Groq) for multi-disease support while B uses a specialized CNN model (TensorFlow/Keras) trained specifically on corn leaves.
About leaf-diseases-detect
shukur-alom/leaf-diseases-detect
AI leaf disease detection system with FastAPI + Streamlit using Llama Vision (Groq) for all diseases, severity and treatment recommendations
Leverages Meta's Llama Vision via Groq API to identify 500+ plant diseases across fungal, bacterial, viral, pest-related, and nutrient deficiency categories with confidence scoring and severity classification. The dual-interface architecture decouples a FastAPI backend service (with auto-generated OpenAPI docs) from a Streamlit frontend, enabling both programmatic API access and interactive web usage. Core features include structured JSON outputs with symptom analysis, environmental factors, and evidence-based treatment protocols, optimized for sub-5-second inference with configurable temperature and token parameters.
About Corn-Leaf-Diseases-Detection
Luissalazarsalinas/Corn-Leaf-Diseases-Detection
Corn leaf diseases detection App built with Tensorflow, Keras and Streamlit
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