===== HW 3 - CNNs =====

All information regarding the third homework assignment can be found here:  
[[https://github.com/urob-ctu/hw3-cnns|UROB HW3 – Fruit Image Analysis Repository]]

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==== 🍎 Overview ====

This homework focuses on training a **Convolutional Neural Network (CNN)** to:
  * 🏷️ **Classify** images of fruits into 30 categories
  * 🎨 **Segment** fruits using pixel-level masks
  * 🔍 **Learn** meaningful image embeddings

The goal is to design, train, and evaluate a model capable of performing all three tasks efficiently.

==== ✅ Tasks ====

  * Implement your CNN model in `model.py` as class `MyModel`
  * The `forward()` method must return:
    - Class logits `[batch_size, 30]`
    - Segmentation mask `[batch_size, 1, 64, 64]`
    - Image embeddings `[batch_size, embedding_dim]`
  * Implement `get_embedding()` returning embeddings only
  * Complete the training loop in `train.py`
  * Tune hyperparameters in `confs/config.yml`

==== 📊 Evaluation ====

**Basic Evaluation (10 points)**

| Task | Metric | Threshold | Points |
|------|---------|------------|--------|
| 🍊 Classification | Accuracy | 80% → 1 pt | 85% → 2 pts |
| 🎨 Segmentation | Mean IoU | 75% → 1 pt | 80% → 2 pts | 85% → 3 pts |
| 📈 Embeddings (ROC) | AUC | 0.80 → 1 pt | 0.85 → 2 pts |
| 🎯 Embeddings (TPR) | TPR @ 5% FPR | 0.75 → 1 pt | 0.80 → 2 pts | 0.85 → 3 pts |

**Tournament Evaluation (up to +5 bonus points)**  
Models are ranked by performance across all tasks.  
Lower total rank = better score.  
Ties are broken by earlier submission.

* 🥇 1st place → +5 pts  
* 🥈 2nd → +4 pts  
* 🥉 3rd → +3 pts  
* 🏅 Top 10 → +2 pts  
* 🎖️ Top 20 → +1 pt  

Maximum total = **15 points**

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==== 📦 Submission ====

Submit a ZIP file containing:
  * `model.py` – your model
  * `train.py` – your training script
  * `weights.pth` – trained model weights

==== 🚫 Important Policies ====

**Pretrained Models Policy**  
❌ No pretrained models or transfer learning allowed.  
✅ Train from scratch using only the provided dataset.

**Plagiarism Policy**  
✅ You may discuss ideas with classmates.  
❌ Direct code copying = 0 points.

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**Good luck! 🍀**  
For questions, contact: hlavsja3@fel.cvut.cz