Python ML Image Classifier
Budget: ₹600 – ₹7,000 INR
I have a collection of general-purpose images and need a complete Python-based pipeline that extracts meaningful features and classifies each image accurately. The project centres on image feature extraction and subsequent classification, so solid experience with OpenCV, scikit-learn or a deep-learning stack such as TensorFlow or PyTorch is essential.
You will begin by deciding on (and justifying) an appropriate feature strategy—traditional descriptors like SIFT/ORB, transfer-learning from a CNN, or another proven method—then train and validate a classifier that reaches reliable accuracy on a held-out test set. Clean, well-commented code and clear, reproducible training steps are critical because I need to retrain the model as new data arrives.
Deliverables
• Python source (scripts or Google Colab file ) covering preprocessing, feature extraction, model training and evaluation
• Saved, ready-to-use model weights/checkpoints
• README with environment setup, run commands and a brief explanation of design decisions
• Short report that includes accuracy metrics, confusion matrix and any visualisations used for validation
If this aligns with your skill set, let me know how you would approach the feature extraction stage and which libraries you plan to leverage.
You will begin by deciding on (and justifying) an appropriate feature strategy—traditional descriptors like SIFT/ORB, transfer-learning from a CNN, or another proven method—then train and validate a classifier that reaches reliable accuracy on a held-out test set. Clean, well-commented code and clear, reproducible training steps are critical because I need to retrain the model as new data arrives.
Deliverables
• Python source (scripts or Google Colab file ) covering preprocessing, feature extraction, model training and evaluation
• Saved, ready-to-use model weights/checkpoints
• README with environment setup, run commands and a brief explanation of design decisions
• Short report that includes accuracy metrics, confusion matrix and any visualisations used for validation
If this aligns with your skill set, let me know how you would approach the feature extraction stage and which libraries you plan to leverage.