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README.md

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+---
+license: mit
+tags:
+  - image-segmentation
+  - food-segmentation
+  - pytorch
+  - segmentation-models-pytorch
+  - deeplabv3plus
+  - mobilenetv2
+datasets:
+  - foodseg103
+metrics:
+  - iou
+library_name: segmentation-models-pytorch
+---
+
+# Food Segmentation Model (DeepLabV3+ with MobileNetV2)
+
+A semantic segmentation model trained on the FoodSeg103 dataset for food image segmentation.
+
+## Model Description
+
+- **Architecture:** DeepLabV3+ with MobileNetV2 encoder
+- **Backbone:** MobileNetV2 (pretrained on ImageNet)
+- **Task:** Semantic Segmentation
+- **Dataset:** FoodSeg103 (103 food categories + background)
+- **Input Size:** 512x512 RGB images
+- **Output:** 104-class segmentation mask
+
+## Training Details
+
+| Metric | Value |
+|--------|-------|
+| **Best Validation Loss** | 0.9726 |
+| **Best Validation mIoU** | 23.33% |
+| **Training Epochs** | 44 |
+| **Optimizer** | AdamW (lr=1e-4, weight_decay=1e-2) |
+| **Scheduler** | CosineAnnealingWarmRestarts |
+| **Loss Function** | Dice Loss + Cross Entropy |
+| **Batch Size** | 16 |
+
+## Usage
+
+```python
+import torch
+import segmentation_models_pytorch as smp
+from huggingface_hub import hf_hub_download
+
+# Download model weights
+model_path = hf_hub_download(
+    repo_id="mawiie/food-segmentation-mobilenet",
+    filename="best_model.pth"
+)
+
+# Create model architecture
+model = smp.DeepLabV3Plus(
+    encoder_name="mobilenet_v2",
+    encoder_weights=None,  # We'll load our own weights
+    in_channels=3,
+    classes=104,
+)
+
+# Load trained weights
+model.load_state_dict(torch.load(model_path, map_location="cpu"))
+model.eval()
+
+# Inference
+# Normalize with ImageNet stats: mean=(0.485, 0.456, 0.406), std=(0.229, 0.224, 0.225)
+# Input shape: (B, 3, 512, 512)
+# Output shape: (B, 104, 512, 512)
+```
+
+## Data Augmentation
+
+**Training:**
+- Horizontal flip (p=0.5)
+- Vertical flip (p=0.1)
+- Affine transforms (scale, rotate, shear)
+- Random crop to 512x512
+- Color augmentations (brightness, contrast, HSV)
+- Gaussian blur
+
+**Validation:**
+- Center crop to 512x512
+
+## Framework
+
+- PyTorch
+- segmentation-models-pytorch
+- Albumentations
+
+## License
+
+MIT License