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7 changes: 7 additions & 0 deletions model-zoo/README.md
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# Generative Models - Model Zoo

In this directory, we include the prototypes of the model zoo for the MONAI Generative Models project.
Different from the official one, we do not include all features from the [official one](https://github.com/Project-MONAI/model-zoo).
For this reason, it is not possible to download the models directly with the `python -m monai.bundle run ...` command.
In order to use our models, please, manually download them with their link specified in the `large_files.yml` files,
and place them inside the folder path specified in the same .yml file.
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false,
false
],
"with_encoder_nonlocal_attn": true,
"with_decoder_nonlocal_attn": true
"with_encoder_nonlocal_attn": false,
"with_decoder_nonlocal_attn": false
},
"load_autoencoder_path": "$@model_dir + '/autoencoder.pth'",
"load_autoencoder": "$@autoencoder_def.load_state_dict(torch.load(@load_autoencoder_path))",
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"schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_20220324.json",
"version": "1.0.0",
"changelog": {
"0.1": "Initial release"
"0.2": "Flipped images fixed"
},
"monai_version": "1.1.0",
"pytorch_version": "1.13.0",
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Expand Up @@ -12,7 +12,11 @@ This model is trained from scratch using the Latent Diffusion Model architecture
2D Chest X-ray conditioned on Radiological reports. The model is divided into two parts: an autoencoder with a
KL-regularisation model that compresses data into a latent space and a diffusion model that learns to generate
conditioned synthetic latent representations. This model is conditioned on Findings and Impressions from radiological
reports.
reports. The original repository can be found [here](https://github.com/Warvito/generative_chestxray)

![](./figure_1.png) <br>
<p align="center">
Figure 1 - Synthetic images from the model. </p>

## **Data**
The model was trained on brain data from 90,000 participants from the MIMIC dataset [2] [3]. We downsampled the
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large_files:
- path: "models/autoencoder.pth"
url: "https://drive.google.com/uc?export=download&id=11Em6qkEsqbFrtJau2mlZAvQZqQmiIEVe"
url: "https://drive.google.com/uc?export=download&id=1paDN1m-Q_Oy8d_BanPkRTi3RlNB_Sv_h"
hash_val: ""
hash_type: ""
- path: "models/diffusion_model.pth"
url: "https://drive.google.com/uc?export=download&id=1PUqHb_0dKB7GAXA3P8l_3pIyorLudgrB"
url: "https://drive.google.com/uc?export=download&id=1CjcmiPu5_QWr-f7wDJsXrCCcVeczneGT"
hash_val: ""
hash_type: ""