Crop Health and market linkage - 27/08/2026 09:29 EDT

Python, Mobile App Development, Photoshop, Software Architecture, Machine Learning (ML), Data Science, Image Processing, Data Visualization, Data Analysis, Deep Learning · I’m building a lightweight AI proof-of-concept that helps farmers monitor crop health and estimate likely yields. My immediate focus is on two functions:

• Disease detection – flag visible leaf symptoms from the images I already have. • Yield prediction – provide a first-pass estimate based on those same images.

Only images of crops are available right now, so the solution should rely on computer-vision techniques (Python with TensorFlow or PyTorch is fine). I need:

1. A well-commented notebook or script that trains and tests both models on my dataset. 2. Clear instructions for retraining with new images. 3. Basic performance metrics (accuracy / F1 or similar) on a held-out sample. 4. A short README outlining next-step recommendations for adding soil, weather, or sensor data as we expand toward irrigation management and market-linkage features.

Keep the code modular and lightweight so it can eventually run on a modest cloud instance or edge device. Deliver everything in a shared repo or zip file within a week, and feel free to suggest any open-source libraries or pre-trained networks that speed things up while staying within a small footprint.