Model Integration Request for medigan: 00020_PGGAN_CHEST_XRAY

[RichardObi]

Creator: Bradley Segal, Medigan Model Preparation: Richard Osuala, Scoayna Jouide Affiliation: University of the Witwatersrand Stored in: https://zenodo.org/record/7046281

Model Metadata:

   "00020_PGGAN_CHEST_XRAY": {
      "execution": {
         "package_name": "00020_PGGAN_CHEST_XRAY",
         "package_link": "https://zenodo.org/record/7046281/files/00020_PGGAN_CHEST_XRAY.zip?download=1",
         "model_name": "Final_Full_Model",
         "extension": ".pth",
         "image_size": [
            1024,
            1024,
            3
         ],
         "dependencies": [
            "pytorch_lightning==1.2.10",
            "torch",
            "torchvision",
            "matplotlib",
            "pillow",
            "numpy"
         ],
         "generate_method": {
            "name": "generate",
            "args": {
               "base": [
                  "model_file",
                  "num_samples",
                  "output_path",
                  "save_images"
               ],
               "custom": {
                  "image_size": 1024,
                  "resize_pixel_dim": null
               }
            },
            "input_latent_vector_size": 512
         }
      },
      "selection": {
         "performance": {
            "SSIM": null,
            "MSE": null,
            "NSME": null,
            "PSNR": null,
            "IS": null,
            "FID": null,
            "turing_test": null,
            "downstream_task": null
         },
         "use_cases": [
            "classification",
            "detection"
         ],
         "organ": [
            "lung",
            "chest",
            "thorax"
         ],
         "modality": [
            "x-ray",
            "xray",
            "CXR"
         ],
         "vendors": [],
         "centres": [],
         "function": [
            "noise to image",
            "unconditional generation",
            "data augmentation"
         ],
         "condition": [],
         "dataset": [
            "ChestX-ray14"
         ],
         "augmentations": [],
         "generates": [
            "chest xray",
            "CXR",
            "thoracic xray",
            "lung xray",
            "lung xray"
         ],
         "height": 1028,
         "width": 1028,
         "depth": 3,
         "type": "PGGAN",
         "license": null,
         "dataset_type": "public",
         "privacy_preservation": null,
         "tags": [
            "Thoracic xray",
            "xray",
            "x-ray",
            "Thorax",
            "Lung",
            "Nodules",
            "Lung Cancer",
            "Lung Tumor"
         ],
         "year": "2022"
      },
      "description": {
         "title": "PGGAN Model for Generation of Chest XRAY (CXR) Images (Trained on ChestX-ray14 Dataset)",
         "provided_date": "September 2022",
         "trained_date": "2021",
         "provided_after_epoch": null,
         "version": null,
         "publication": null,
         "doi": [
            "https://doi.org/10.1007/s42979-021-00720-7"
         ],
         "inputs": [
            "image_size: default=1024, help=the size if height and width of the generated images",
            "resize_pixel_dim: default=None, help=Resizing of generated images via the pillow PIL image library."
         ],
         "comment": "A unconditional Progressively-growing generative adversarial network (PGGAN) that generates chest xray (CXR) images with pixel dimensions 1024x1024. The PGGAN was trained on CXR images based on ChestX-ray14 dataset (Wang et al. 2017, Paper: https://arxiv.org/pdf/1705.02315.pdf, Data: https://nihcc.app.box.com/v/ChestXray-NIHCC). The uploaded ZIP file contains the model weights checkpoint file, __init__.py (image generation method and utils), a requirements.txt, the MEDIGAN metadata.json file, a test.sh file to run the model, and an /image folder with a few generated example images."
      }
   }
}

[RichardObi]

Model is being integrated