metadata
datasets:
- hongrui/mimic_chest_xray_v_1
🩺 CheXNet-MedScan-Report-Gen
CheXNet-MedScan-Report-Gen is an image captioning model for generating diagnostic text reports from chest X-ray images. It combines the power of a pretrained CheXNet encoder (based on DenseNet121) and a bidirectional LSTM decoder to produce sequence-based textual descriptions.
🧠 Model Architecture
- Encoder: DenseNet121 (CheXNet) with classifier removed
- Decoder: Bidirectional LSTM with dropout
- Feature dimension: 1024
- Embedding dimension: 256
- Hidden dimension: 512
- Vocabulary size: 5000
- Dropout: 0.5
🔧 Usage
You can load the model using the Hugging Face Transformers library:
from transformers import AutoTokenizer, AutoConfig
from modeling import ImageCaptioningModel
config = AutoConfig.from_pretrained("khalednabawi11/Chexnet-MedScan-Report-Gen")
model = ImageCaptioningModel.from_pretrained("khalednabawi11/Chexnet-MedScan-Report-Gen", config=config)