Initial model upload

.gitattributes

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+*.safetensors filter=lfs diff=lfs merge=lfs -text

LICENSE

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+
+---
+
+```text
+MIT License
+
+Copyright (c) 2025 OM KUMAR
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

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+---
+language: en
+tags:
+- vision
+- densenet
+- densenet121
+- chexpert
+- chest-xray
+- multi-label
+- classification
+- safetensors
+- pytorch
+license: mit
+pipeline_tag: image-classification
+author: Om Kumar (@itsomk)
+---
+# DenseNet121 CheXpert Multi-label (chexpert-densenet121-v1)
+
+## Model Description
+This model is a fine-tuned **DenseNet-121** (PyTorch) for **multi-label classification of chest X-rays**, trained on the Stanford **CheXpert v1.0** dataset.  
+It predicts the presence of the following 14 labels (order preserved):
+
+- No Finding  
+- Enlarged Cardiomediastinum  
+- Cardiomegaly  
+- Lung Opacity  
+- Lung Lesion  
+- Edema  
+- Consolidation  
+- Pneumonia  
+- Atelectasis  
+- Pneumothorax  
+- Pleural Effusion  
+- Pleural Other  
+- Fracture  
+- Support Devices  
+
+**Author:** Om Kumar (Hugging Face: [@itsomk](https://huggingface.co/itsomk))  
+
+**Model files included:**  
+- `chexpert_pytorch.safetensors` — model weights saved with `safetensors`  
+- `config.json` — minimal config (backbone, num_labels, transforms)  
+- `training_history.png` — training curves
+
+> ⚠️ **Important:**  This model is provided **for research and educational purposes only**. Not for clinical use.
+
+---
+
+## Intended Use
+- Research in medical imaging and multi-label classification  
+- Educational use and reproducible baseline for further fine-tuning or adaptation  
+- NOT intended for clinical diagnosis or patient care. Use with caution; validate thoroughly before any downstream application.
+
+---
+
+## Training Summary
+- **Backbone:** DenseNet-121 (PyTorch `torchvision.models.densenet121`)  
+- **Dataset:** CheXpert v1.0 (Stanford)  
+- **Uncertainty handling:** U-Zeros (replace -1 with 0)  
+- **Image size:** 224 × 224  
+- **Epochs:** 20  
+- **Batch size:** 32  
+- **Optimizer:** Adam (lr=1e-4, weight_decay=1e-4)  
+- **Loss:** BCEWithLogitsLoss with per-class pos_weight  
+- **Best validation mean AUC:** **0.8176**
+
+### Per-class AUC (validation)
+- No Finding : 0.8762  
+- Enlarged Cardiomediastinum : 0.5959  
+- Cardiomegaly : 0.8165  
+- Lung Opacity : 0.8083  
+- Lung Lesion : 0.8230  
+- Edema : 0.8779  
+- Consolidation : 0.8527  
+- Pneumonia : 0.7559  
+- Atelectasis : 0.7117  
+- Pneumothorax : 0.8546  
+- Pleural Effusion : 0.9021  
+- Pleural Other : 0.9157  
+- Fracture : 0.7936  
+- Support Devices : 0.8622
+
+---
+
+## Quick Usage (local safetensors)
+
+```python
+
+import torch
+from torchvision import models, transforms
+from safetensors.torch import load_file
+from huggingface_hub import hf_hub_download
+from PIL import Image
+
+REPO_ID = "itsomk/chexpert-densenet121"
+FILENAME = "pytorch_model.safetensors"
+
+
+local_path = hf_hub_download(repo_id=REPO_ID, filename=FILENAME)
+
+
+class DenseNet121_CheXpert(torch.nn.Module):
+    def __init__(self, num_labels=14, pretrained=False):
+        super().__init__()
+        self.densenet = models.densenet121(pretrained=pretrained)
+        num_features = self.densenet.classifier.in_features
+        self.densenet.classifier = torch.nn.Linear(num_features, num_labels)
+    def forward(self, x):
+        return self.densenet(x)
+
+
+state = load_file(local_path)  
+
+model = DenseNet121_CheXpert(num_labels=14, pretrained=False)
+
+model.load_state_dict(state, strict=False)
+model.eval()
+
+
+preprocess = transforms.Compose([
+    transforms.Resize((224, 224)),
+    transforms.ToTensor(),
+    transforms.Normalize(mean=[0.485,0.456,0.406], std=[0.229,0.224,0.225])
+])
+
+
+labels = [
+ "No Finding","Enlarged Cardiomediastinum","Cardiomegaly","Lung Opacity",
+ "Lung Lesion","Edema","Consolidation","Pneumonia","Atelectasis",
+ "Pneumothorax","Pleural Effusion","Pleural Other","Fracture","Support Devices"
+]
+
+# inference
+img = Image.open("path/to/xray.jpg").convert("RGB")
+x = preprocess(img).unsqueeze(0)  
+with torch.no_grad():
+    logits = model(x)
+    probs = torch.sigmoid(logits).squeeze().tolist()
+
+results = {labels[i]: float(probs[i]) for i in range(len(labels))}
+print(results)
+

config.json

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+{
+  "model_type": "densenet",
+  "architectures": ["DenseNet121"],
+  "num_labels": 14,
+  "labels": [
+    "No Finding",
+    "Enlarged Cardiomediastinum",
+    "Cardiomegaly",
+    "Lung Opacity",
+    "Lung Lesion",
+    "Edema",
+    "Consolidation",
+    "Pneumonia",
+    "Atelectasis",
+    "Pneumothorax",
+    "Pleural Effusion",
+    "Pleural Other",
+    "Fracture",
+    "Support Devices"
+  ],
+  "id2label": {
+    "0": "No Finding",
+    "1": "Enlarged Cardiomediastinum",
+    "2": "Cardiomegaly",
+    "3": "Lung Opacity",
+    "4": "Lung Lesion",
+    "5": "Edema",
+    "6": "Consolidation",
+    "7": "Pneumonia",
+    "8": "Atelectasis",
+    "9": "Pneumothorax",
+    "10": "Pleural Effusion",
+    "11": "Pleural Other",
+    "12": "Fracture",
+    "13": "Support Devices"
+  },
+  "label2id": {
+    "No Finding": 0,
+    "Enlarged Cardiomediastinum": 1,
+    "Cardiomegaly": 2,
+    "Lung Opacity": 3,
+    "Lung Lesion": 4,
+    "Edema": 5,
+    "Consolidation": 6,
+    "Pneumonia": 7,
+    "Atelectasis": 8,
+    "Pneumothorax": 9,
+    "Pleural Effusion": 10,
+    "Pleural Other": 11,
+    "Fracture": 12,
+    "Support Devices": 13
+  }
+}

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