Initial upload of Wargon Clothing Classifier v1.0

README.md

@@ -0,0 +1,229 @@
+---
+license: apache-2.0
+base_model: google/vit-base-patch16-224
+tags:
+- image-classification
+- vision
+- clothing
+- fashion
+- vit
+- pytorch
+datasets:
+- wargoninnovation/clothingdatasetsecondhand
+metrics:
+- accuracy
+- f1
+pipeline_tag: image-classification
+widget:
+- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg
+  example_title: Tiger
+---
+
+# Wargon Clothing Classifier
+
+A Vision Transformer (ViT) based model for clothing classification, trained on secondhand clothing images. This model can classify 27 different types of clothing items with 73% accuracy.
+
+## Model Details
+
+### Model Description
+
+This is a Vision Transformer model fine-tuned for clothing classification. It was developed to solve real-world clothing categorization challenges in secondhand fashion applications.
+
+- **Developed by:** Wargon Innovation
+- **Model type:** Image Classification
+- **Language(s):** N/A (Vision model)
+- **License:** Apache 2.0
+- **Finetuned from model:** google/vit-base-patch16-224
+
+### Model Sources
+
+- **Repository:** [Wargon Innovation Clothing Dataset](https://huggingface.co/datasets/wargoninnovation/clothingdatasetsecondhand)
+- **Base Model:** [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224)
+
+## Uses
+
+### Direct Use
+
+This model can be used for:
+- Automatic clothing categorization in e-commerce
+- Fashion inventory management
+- Secondhand clothing marketplaces
+- Fashion recommendation systems
+
+### Downstream Use
+
+The model can be fine-tuned for:
+- Specific clothing brand recognition
+- Size estimation from images
+- Style classification
+- Multi-label clothing attribute detection
+
+## How to Get Started with the Model
+
+```python
+from transformers import AutoImageProcessor, AutoModelForImageClassification
+from PIL import Image
+import torch
+
+# Load model and processor
+processor = AutoImageProcessor.from_pretrained("wargoninnovation/wargon-clothing-classifier")
+model = AutoModelForImageClassification.from_pretrained("wargoninnovation/wargon-clothing-classifier")
+
+# Load and preprocess image
+image = Image.open("path_to_clothing_image.jpg")
+inputs = processor(image, return_tensors="pt")
+
+# Make prediction
+with torch.no_grad():
+    outputs = model(**inputs)
+    predictions = torch.nn.functional.softmax(outputs.logits, dim=-1)
+
+# Get top prediction
+predicted_class_id = predictions.argmax().item()
+```
+
+## Training Details
+
+### Training Data
+
+The model was trained on the [wargoninnovation/clothingdatasetsecondhand](https://huggingface.co/datasets/wargoninnovation/clothingdatasetsecondhand) dataset, which contains over 30,000 images of secondhand clothing items across 34+ categories.
+
+**Data Preprocessing:**
+- Filtered classes with fewer than 10 samples to ensure robust train/validation splits
+- Final dataset contains 27 clothing categories
+- Images resized to 224x224 pixels
+- Stratified train/validation split (80/20)
+
+### Training Procedure
+
+#### Preprocessing
+
+- **Image Size:** 224x224 pixels
+- **Normalization:** ImageNet statistics
+- **Data Augmentation:** Standard transformations applied
+
+#### Training Hyperparameters
+
+- **Training regime:** Mixed precision (fp16)
+- **Learning Rate:** 2e-5
+- **Batch Size:** 16
+- **Epochs:** 6
+- **Optimizer:** AdamW
+- **Weight Decay:** 0.01
+- **Warmup Steps:** 500
+- **Label Smoothing:** 0.1
+
+#### Hardware
+
+- **GPU:** NVIDIA RTX 3060 (12GB VRAM)
+- **Training Time:** ~1.5 hours
+
+## Evaluation
+
+### Testing Data, Factors & Metrics
+
+The model was evaluated on a stratified validation set (20% of the filtered dataset).
+
+#### Metrics
+
+- **Validation Accuracy:** 73.0%
+- **F1 Score:** 72.7%
+- **Precision:** 72.8%
+- **Recall:** 73.0%
+
+### Results
+
+The model achieves balanced performance across major clothing categories, with particular strength in:
+- Common items (T-shirts, Jeans, Dresses)
+- Well-represented categories in the training data
+- Clean product photography (as in the training dataset)
+
+## Clothing Categories
+
+The model can classify the following 27 clothing types:
+
+1. Blazer
+2. Blouse
+3. Cardigan
+4. Dress
+5. Hoodie
+6. Jacket
+7. Jeans
+8. Nightgown
+9. Outerwear
+10. Pajamas
+11. Rain jacket
+12. Rain trousers
+13. Robe
+14. Shirt
+15. Shorts
+16. Skirt
+17. Sweater
+18. T-shirt
+19. Tank top
+20. Tights
+21. Top
+22. Training top
+23. Trousers
+24. Tunic
+25. Vest
+26. Winter jacket
+27. Winter trousers
+
+## Limitations and Bias
+
+### Limitations
+
+- **Image Quality:** Best performance on clean, well-lit product photos similar to training data
+- **Background:** Optimized for images with minimal background distractions
+- **Viewpoint:** Trained primarily on front-facing clothing images
+- **Categories:** Limited to the 27 categories present in training data
+
+### Bias
+
+- **Data Source:** Trained on secondhand clothing, may not generalize well to new/luxury items
+- **Cultural Bias:** Dataset may reflect specific regional fashion preferences
+- **Class Imbalance:** Some categories had limited representation even after filtering
+
+## Environmental Impact
+
+- **Hardware Type:** NVIDIA RTX 3060
+- **Hours Used:** ~1.5 hours training time
+- **Cloud Provider:** N/A (Local training)
+- **Compute Region:** Local
+
+## Technical Specifications
+
+### Model Architecture
+
+- **Base:** Vision Transformer (ViT-Base/16)
+- **Parameters:** ~86M parameters
+- **Input Size:** 224x224x3
+- **Patch Size:** 16x16
+- **Number of Classes:** 27
+
+### Software
+
+- **Framework:** PyTorch
+- **Libraries:** HuggingFace Transformers, Datasets
+- **Training Libraries:** Weights & Biases (W&B)
+
+## Citation
+
+```bibtex
+@misc{wargon_clothing_classifier_2024,
+  title={Wargon Clothing Classifier: A Vision Transformer for Secondhand Fashion Classification},
+  author={Wargon Innovation},
+  year={2024},
+  publisher={Hugging Face},
+  howpublished={\url{https://huggingface.co/wargoninnovation/wargon-clothing-classifier}},
+}
+```
+
+## Model Card Authors
+
+Wargon Innovation Team
+
+## Model Card Contact
+
+For questions and feedback, please open an issue in the model repository or contact the Wargon Innovation team.

class_mappings.json

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+{
+  "class_to_id": {
+    "Blazer": 0,
+    "Blouse": 1,
+    "Cardigan": 2,
+    "Dress": 3,
+    "Hoodie": 4,
+    "Jacket": 5,
+    "Jeans": 6,
+    "Nightgown": 7,
+    "Outerwear": 8,
+    "Pajamas": 9,
+    "Rain jacket": 10,
+    "Rain trousers": 11,
+    "Robe": 12,
+    "Shirt": 13,
+    "Shorts": 14,
+    "Skirt": 15,
+    "Sweater": 16,
+    "T-shirt": 17,
+    "Tank top": 18,
+    "Tights": 19,
+    "Top": 20,
+    "Training top": 21,
+    "Trousers": 22,
+    "Tunic": 23,
+    "Vest": 24,
+    "Winter jacket": 25,
+    "Winter trousers": 26
+  },
+  "id_to_class": {
+    "0": "Blazer",
+    "1": "Blouse",
+    "2": "Cardigan",
+    "3": "Dress",
+    "4": "Hoodie",
+    "5": "Jacket",
+    "6": "Jeans",
+    "7": "Nightgown",
+    "8": "Outerwear",
+    "9": "Pajamas",
+    "10": "Rain jacket",
+    "11": "Rain trousers",
+    "12": "Robe",
+    "13": "Shirt",
+    "14": "Shorts",
+    "15": "Skirt",
+    "16": "Sweater",
+    "17": "T-shirt",
+    "18": "Tank top",
+    "19": "Tights",
+    "20": "Top",
+    "21": "Training top",
+    "22": "Trousers",
+    "23": "Tunic",
+    "24": "Vest",
+    "25": "Winter jacket",
+    "26": "Winter trousers"
+  },
+  "num_classes": 27,
+  "valid_classes": [
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+}

config.json

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+{
+  "architectures": [
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+  "attention_probs_dropout_prob": 0.0,
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+  "problem_type": "single_label_classification",
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+  "torch_dtype": "float32",
+  "transformers_version": "4.55.3"
+}

model.safetensors

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+size 343300876

preprocessor_config.json

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