From c80a92ae4a07ab60944a1a8f86ea1a9faafd71d3 Mon Sep 17 00:00:00 2001 From: Virginia Date: Mon, 9 Dec 2024 16:04:28 +0000 Subject: [PATCH 1/6] Initial commit of CXR Latent Diffusion model from the GenerativeModels repo. Signed-off-by: Virginia --- .../LICENSE | 201 ++++++++++++++++++ .../configs/inference.json | 108 ++++++++++ .../configs/logging.conf | 21 ++ .../configs/metadata.json | 73 +++++++ .../docs/README.md | 76 +++++++ .../docs/figure_1.png | Bin 0 -> 478177 bytes .../large_files.yml | 9 + .../scripts/__init__.py | 0 .../scripts/sampler.py | 43 ++++ .../scripts/saver.py | 17 ++ 10 files changed, 548 insertions(+) create mode 100644 models/cxr_image_synthesis_latent_diffusion_model/LICENSE create mode 100644 models/cxr_image_synthesis_latent_diffusion_model/configs/inference.json create mode 100644 models/cxr_image_synthesis_latent_diffusion_model/configs/logging.conf create mode 100644 models/cxr_image_synthesis_latent_diffusion_model/configs/metadata.json create mode 100644 models/cxr_image_synthesis_latent_diffusion_model/docs/README.md create mode 100644 models/cxr_image_synthesis_latent_diffusion_model/docs/figure_1.png create mode 100644 models/cxr_image_synthesis_latent_diffusion_model/large_files.yml create mode 100644 models/cxr_image_synthesis_latent_diffusion_model/scripts/__init__.py create mode 100644 models/cxr_image_synthesis_latent_diffusion_model/scripts/sampler.py create mode 100644 models/cxr_image_synthesis_latent_diffusion_model/scripts/saver.py diff --git a/models/cxr_image_synthesis_latent_diffusion_model/LICENSE b/models/cxr_image_synthesis_latent_diffusion_model/LICENSE new file mode 100644 index 00000000..261eeb9e --- /dev/null +++ b/models/cxr_image_synthesis_latent_diffusion_model/LICENSE @@ -0,0 +1,201 @@ + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. 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/dev/null +++ b/models/cxr_image_synthesis_latent_diffusion_model/configs/inference.json @@ -0,0 +1,108 @@ +{ + "imports": [ + "$import torch", + "$from datetime import datetime", + "$from pathlib import Path", + "$from transformers import CLIPTextModel", + "$from transformers import CLIPTokenizer" + ], + "bundle_root": ".", + "load_old": 1, + "model_dir": "$@bundle_root + '/models'", + "output_dir": "$@bundle_root + '/output'", + "create_output_dir": "$Path(@output_dir).mkdir(exist_ok=True)", + "prompt": "Big right-sided pleural effusion", + "prompt_list": "$['', @prompt]", + "guidance_scale": 7.0, + "device": "$torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')", + "tokenizer": "$CLIPTokenizer.from_pretrained(\"stabilityai/stable-diffusion-2-1-base\", subfolder=\"tokenizer\")", + "text_encoder": "$CLIPTextModel.from_pretrained(\"stabilityai/stable-diffusion-2-1-base\", subfolder=\"text_encoder\")", + "tokenized_prompt": "$@tokenizer(@prompt_list, padding=\"max_length\", max_length=@tokenizer.model_max_length, truncation=True,return_tensors=\"pt\")", + "prompt_embeds": "$@text_encoder(@tokenized_prompt.input_ids.squeeze(1))[0].to(@device)", + "out_file": "$datetime.now().strftime('sample_%H%M%S_%d%m%Y')", + "autoencoder_def": { + "_target_": "monai.networks.nets.AutoencoderKL", + "spatial_dims": 2, + "in_channels": 1, + "out_channels": 1, + "latent_channels": 3, + "channels": [ + 64, + 128, + 128, + 128 + ], + "num_res_blocks": 2, + "norm_num_groups": 32, + "norm_eps": 1e-06, + "attention_levels": [ + false, + false, + false, + false + ], + "with_encoder_nonlocal_attn": false, + "with_decoder_nonlocal_attn": false + }, + "load_autoencoder_path": "$@model_dir + '/autoencoder.pth'", + "load_autoencoder": "$@autoencoder_def.load_old_state_dict(torch.load(@load_autoencoder_path)) if bool(@load_old) else @autoencoder_def.load_state_dict(torch.load(@load_autoencoder_path))", + "autoencoder": "$@autoencoder_def.to(@device)", + "diffusion_def": { + "_target_": "monai.networks.nets.DiffusionModelUNet", + "spatial_dims": 2, + "in_channels": 3, + "out_channels": 3, + "channels": [ + 256, + 512, + 768 + ], + "num_res_blocks": 2, + "attention_levels": [ + false, + true, + true + ], + "norm_num_groups": 32, + "norm_eps": 1e-06, + "resblock_updown": false, + "num_head_channels": [ + 0, + 512, + 768 + ], + "with_conditioning": true, + "transformer_num_layers": 1, + "cross_attention_dim": 1024 + }, + "load_diffusion_path": "$@model_dir + '/diffusion_model.pth'", + "load_diffusion": "$@diffusion_def.load_old_state_dict(torch.load(@load_diffusion_path)) if bool(@load_old) else @diffusion_def.load_state_dict(torch.load(@load_diffusion_path))", + "diffusion": "$@diffusion_def.to(@device)", + "scheduler": { + "_target_": "monai.networks.schedulers.DDIMScheduler", + "_requires_": [ + "@load_diffusion", + "@load_autoencoder" + ], + "beta_start": 0.0015, + "beta_end": 0.0205, + "num_train_timesteps": 1000, + "schedule": "scaled_linear_beta", + "prediction_type": "v_prediction", + "clip_sample": false + }, + "noise": "$torch.randn((1, 3, 64, 64)).to(@device)", + "set_timesteps": "$@scheduler.set_timesteps(num_inference_steps=50)", + "sampler": { + "_target_": "scripts.sampler.Sampler", + "_requires_": "@set_timesteps" + }, + "sample": "$@sampler.sampling_fn(@noise, @autoencoder, @diffusion, @scheduler, @prompt_embeds)", + "saver": { + "_target_": "scripts.saver.JPGSaver", + "_requires_": "@create_output_dir", + "output_dir": "@output_dir" + }, + "save_jpg": "$@saver.save(@sample, @out_file)", + "save": "$torch.save(@sample, @output_dir + '/' + @out_file + '.pt')" +} diff --git a/models/cxr_image_synthesis_latent_diffusion_model/configs/logging.conf b/models/cxr_image_synthesis_latent_diffusion_model/configs/logging.conf new file mode 100644 index 00000000..91c1a21c --- /dev/null +++ b/models/cxr_image_synthesis_latent_diffusion_model/configs/logging.conf @@ -0,0 +1,21 @@ +[loggers] +keys=root + +[handlers] +keys=consoleHandler + +[formatters] +keys=fullFormatter + +[logger_root] +level=INFO +handlers=consoleHandler + +[handler_consoleHandler] +class=StreamHandler +level=INFO +formatter=fullFormatter +args=(sys.stdout,) + +[formatter_fullFormatter] +format=%(asctime)s - %(name)s - %(levelname)s - %(message)s diff --git a/models/cxr_image_synthesis_latent_diffusion_model/configs/metadata.json b/models/cxr_image_synthesis_latent_diffusion_model/configs/metadata.json new file mode 100644 index 00000000..020005e3 --- /dev/null +++ b/models/cxr_image_synthesis_latent_diffusion_model/configs/metadata.json @@ -0,0 +1,73 @@ +{ + "schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_20220324.json", + "version": "1.0.0", + "changelog": { + "0.2": "Flipped images fixed" + }, + "monai_version": "1.1.0", + "pytorch_version": "1.13.0", + "numpy_version": "1.22.4", + "optional_packages_version": { + "nibabel": "4.0.1", + "generative": "0.1.0", + "transformers": "4.26.1" + }, + "task": "Chest X-ray image synthesis", + "description": "A generative model for creating high-resolution chest X-ray based on MIMIC dataset", + "copyright": "Copyright (c) MONAI Consortium", + "data_source": "https://physionet.org/content/mimic-cxr-jpg/2.0.0/", + "data_type": "image", + "image_classes": "Radiography (X-ray) with 512 x 512 pixels", + "intended_use": "This is a research tool/prototype and not to be used clinically", + "network_data_format": { + "inputs": { + "latent_representation": { + "type": "image", + "format": "magnitude", + "modality": "CXR", + "num_channels": 3, + "spatial_shape": [ + 64, + 64 + ], + "dtype": "float32", + "value_range": [], + "is_patch_data": false + }, + "timesteps": { + "type": "vector", + "value_range": [ + 0, + 1000 + ], + "dtype": "long" + }, + "context": { + "type": "vector", + "value_range": [], + "dtype": "float32" + } + }, + "outputs": { + "pred": { + "type": "image", + "format": "magnitude", + "modality": "CXR", + "num_channels": 1, + "spatial_shape": [ + 512, + 512 + ], + "dtype": "float32", + "value_range": [ + 0, + 1 + ], + "is_patch_data": false, + "channel_def": { + "0": "X-ray" + } + } + } + } +} diff --git a/models/cxr_image_synthesis_latent_diffusion_model/docs/README.md b/models/cxr_image_synthesis_latent_diffusion_model/docs/README.md new file mode 100644 index 00000000..8680f33b --- /dev/null +++ b/models/cxr_image_synthesis_latent_diffusion_model/docs/README.md @@ -0,0 +1,76 @@ +# Description + +A diffusion model to synthetise X-Ray images based on radiological report impressions. + +# Model Overview +This model is trained from scratch using the Latent Diffusion Model architecture [1] and is used for the synthesis of +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. The original repository can be found [here](https://github.com/Warvito/generative_chestxray) + +![](./figure_1.png)
+

+Figure 1 - Synthetic images from the model.

+ +# Data +The model was trained on brain data from 90,000 participants from the MIMIC dataset [2] [3]. We downsampled the +original images to have a format of 512 x 512 pixels. + +## Preprocessing +We resized the original images to make the smallest sides have 512 pixels. When inputting it to the network, we center +cropped the images to 512 x 512. The pixel intensity was normalised to be between [0, 1]. The text data was obtained +from associated radiological reports. We randoomly extracted sentences from the findings and impressions sections of the +reports, having a maximum of 5 sentences and 77 tokens. The text was tokenised using the CLIPTokenizer from +transformers package (https://github.com/huggingface/transformers) (pretrained model +"stabilityai/stable-diffusion-2-1-base") and then encoded using CLIPTextModel from the same package and pretrained +model. + +# Examples of inference + +Here we included a few examples of commands to sample images from the model and save them as .jpg files. The available +arguments for this task are: "--prompt" (str) text prompt to condition the model on; "--guidance_scale" (float), the +parameter that controls how much the image generation process follows the text prompt. The higher the value, the more +the image sticks to a given text input (the common range is between 1-21). + +Examples: + +```shell +export PYTHONPATH=$PYTHONPATH:"" +$ python -m monai.bundle run save_jpg --config_file configs/inference.json --prompt "Big right-sided pleural effusion" --guidance_scale 7.0 +``` + +```shell +export PYTHONPATH=$PYTHONPATH:"" +$ python -m monai.bundle run save_jpg --config_file configs/inference.json --prompt "Small right-sided pleural effusion" --guidance_scale 7.0 +``` + +```shell +export PYTHONPATH=$PYTHONPATH:"" +$ python -m monai.bundle run save_jpg --config_file configs/inference.json --prompt "Bilateral pleural effusion" --guidance_scale 7.0 +``` + +```shell +export PYTHONPATH=$PYTHONPATH:"" +$ python -m monai.bundle run save_jpg --config_file configs/inference.json --prompt "Cardiomegaly" --guidance_scale 7.0 +``` + +## Using a new version of the model + +If you want to use the checkpoints from a newly fine-tuned model, you need to set parameter load_old to 0 when you run inference, +to avoid the function load_old_state_dict being called instead of load_state_dict to be called, currently default, as it is +required to load the checkpoint from the original GenerativeModels repository. + +```shell +export PYTHONPATH=$PYTHONPATH:"" +$ python -m monai.bundle run save_jpg --config_file configs/inference.json --prompt "Pleural effusion." --guidance_scale 7.0 --load_old 0 +``` + +## References + + +[1] Pinaya, Walter HL, et al. "Brain imaging generation with latent diffusion models." MICCAI Workshop on Deep Generative Models. Springer, Cham, 2022. + +[2] Johnson, A., Lungren, M., Peng, Y., Lu, Z., Mark, R., Berkowitz, S., & Horng, S. (2019). MIMIC-CXR-JPG - chest radiographs with structured labels (version 2.0.0). PhysioNet. https://doi.org/10.13026/8360-t248. + +[3] Johnson AE, Pollard TJ, Berkowitz S, Greenbaum NR, Lungren MP, Deng CY, Mark RG, Horng S. MIMIC-CXR: A large publicly available database of labeled chest radiographs. arXiv preprint arXiv:1901.07042. 2019 Jan 21. diff --git a/models/cxr_image_synthesis_latent_diffusion_model/docs/figure_1.png b/models/cxr_image_synthesis_latent_diffusion_model/docs/figure_1.png new file mode 100644 index 0000000000000000000000000000000000000000..1baa0adbf322a48ca85f97d58cd452ba7d8eec0b GIT binary patch literal 478177 zcmaHSWmFtZ)F$rk&LD#mJh=N{g9Ud_2(Cc~8z8t7Y_Q-ET!TA=U_pYr1b1h7zui6i zZ-4aZbGxd}?XIf6@;tYq!0L+F7!(+AaB$elN^)9oa0uOSaEO*@2yai;PxcSqZt(6} ziZXE36IA~RNOsa{(r|FK@t98*$Zs;bi;{sm92|kie;53!Ev*k6+-tG2oV1RQ>Cwu; zyz`LnobRRw0ijVEaETYfPp&Exj5V2o#c!p=XG5Rhp#5xeQT zRcw>v$a@P;Q-n|F5d*Yy&t(rMYXLXDad8~scSQ#OT1{umP1?)7{+P@MtlX}4DJpjD zz5W~&sCJG0WV}T&?-Sdi4*0)9%iyO$PlW%|(lRJu%2!Po`9Iy>gzEEet~pZwjrmV- zjh&DAhqU>Bg-;!}#>{yCr{!&gz?KN)e|P(Dcn$eHdjJ1Z`Ro6y@+3pbe@8EHN6&vi z?lylwvHNtJWJKhf3mILR~Am+sTGySAFgw&t$qD1Fq-dt_Qu>L)_;{+~?S?bHTu)p}-@>pex1K2ea3ILB}=E 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z9JyA{%3(9R3ZL(8+)VkYynEmbjlo{$!v%kN)wAfcH%T9H(o20Z&th5Z*?bZ$YI%DP z0cL+3Ff8hyAM5jziG{nh@CmKM$YF{KDCQwb^FJV>Cxmk+BN;})y|L^79?Er~kL04| zOZXZt*_il+s)=o^!C}A8z(W5Zx`s`pRO<48vgpb>Yk$ws;O&%|jw;yzj-l%gRk*mC z1lxRDBY?A0s}h|mgvBWdVkOo;=pn#Yu3$|1a;DTC&OxWy|~WYv1szMo9s__GK4@eR}beE6fOXcuFC};zuW47Sm3bIb&}>Hf;$MlPLSObvoul>~#7$wyiygnIz`Y zEV4vWxABNuG2eysbQ9B3UCsck|CSPqV&*d?Bi|1HM$E$_Z}Zb71QtxVkxuX2mpV63 z&RArM|>EAhChF&xhO$m*0XT&U}PgL{pWuBGBDc5ZgW5Fx^ly@@oyex|h zE*Z)b%oI;9RQrB0@Iacq#4F-dkiG)+=h1rJv84A2yCpG None: + super().__init__() + + @torch.no_grad() + def sampling_fn( + self, + noise: torch.Tensor, + autoencoder_model: nn.Module, + diffusion_model: nn.Module, + scheduler: nn.Module, + prompt_embeds: torch.Tensor, + guidance_scale: float = 7.0, + scale_factor: float = 0.3, + ) -> torch.Tensor: + if has_tqdm: + progress_bar = tqdm(scheduler.timesteps) + else: + progress_bar = iter(scheduler.timesteps) + + for t in progress_bar: + noise_input = torch.cat([noise] * 2) + model_output = diffusion_model( + noise_input, timesteps=torch.Tensor((t,)).to(noise.device).long(), context=prompt_embeds + ) + noise_pred_uncond, noise_pred_text = model_output.chunk(2) + noise_pred = noise_pred_uncond + guidance_scale * (noise_pred_text - noise_pred_uncond) + noise, _ = scheduler.step(noise_pred, t, noise) + + with autocast(): + sample = autoencoder_model.decode_stage_2_outputs(noise / scale_factor) + + return sample diff --git a/models/cxr_image_synthesis_latent_diffusion_model/scripts/saver.py b/models/cxr_image_synthesis_latent_diffusion_model/scripts/saver.py new file mode 100644 index 00000000..05e88722 --- /dev/null +++ b/models/cxr_image_synthesis_latent_diffusion_model/scripts/saver.py @@ -0,0 +1,17 @@ +from __future__ import annotations + +import numpy as np +import torch +from PIL import Image + + +class JPGSaver: + def __init__(self, output_dir: str) -> None: + super().__init__() + self.output_dir = output_dir + + def save(self, image_data: torch.Tensor, file_name: str) -> None: + image_data = np.clip(image_data.cpu().numpy(), 0, 1) + image_data = (image_data * 255).astype(np.uint8) + im = Image.fromarray(image_data[0, 0]) + im.save(self.output_dir + "/" + file_name + ".jpg") From fe87cb46deebcfcb2da87582430592dc398b0199 Mon Sep 17 00:00:00 2001 From: Virginia Date: Mon, 9 Dec 2024 16:08:27 +0000 Subject: [PATCH 2/6] Modify the README.md file as it contained something from the old repo that no longer applies. --- .../docs/README.md | 5 ----- 1 file changed, 5 deletions(-) diff --git a/models/cxr_image_synthesis_latent_diffusion_model/docs/README.md b/models/cxr_image_synthesis_latent_diffusion_model/docs/README.md index 8680f33b..ac87910e 100644 --- a/models/cxr_image_synthesis_latent_diffusion_model/docs/README.md +++ b/models/cxr_image_synthesis_latent_diffusion_model/docs/README.md @@ -36,22 +36,18 @@ the image sticks to a given text input (the common range is between 1-21). Examples: ```shell -export PYTHONPATH=$PYTHONPATH:"" $ python -m monai.bundle run save_jpg --config_file configs/inference.json --prompt "Big right-sided pleural effusion" --guidance_scale 7.0 ``` ```shell -export PYTHONPATH=$PYTHONPATH:"" $ python -m monai.bundle run save_jpg --config_file configs/inference.json --prompt "Small right-sided pleural effusion" --guidance_scale 7.0 ``` ```shell -export PYTHONPATH=$PYTHONPATH:"" $ python -m monai.bundle run save_jpg --config_file configs/inference.json --prompt "Bilateral pleural effusion" --guidance_scale 7.0 ``` ```shell -export PYTHONPATH=$PYTHONPATH:"" $ python -m monai.bundle run save_jpg --config_file configs/inference.json --prompt "Cardiomegaly" --guidance_scale 7.0 ``` @@ -62,7 +58,6 @@ to avoid the function load_old_state_dict being called instead of load_state_dic required to load the checkpoint from the original GenerativeModels repository. ```shell -export PYTHONPATH=$PYTHONPATH:"" $ python -m monai.bundle run save_jpg --config_file configs/inference.json --prompt "Pleural effusion." --guidance_scale 7.0 --load_old 0 ``` From de4e1985192d97a9ef57136de88f25f359d1667b Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Mon, 9 Dec 2024 16:11:53 +0000 Subject: [PATCH 3/6] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- .../docs/README.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/models/cxr_image_synthesis_latent_diffusion_model/docs/README.md b/models/cxr_image_synthesis_latent_diffusion_model/docs/README.md index ac87910e..1f7ce0f2 100644 --- a/models/cxr_image_synthesis_latent_diffusion_model/docs/README.md +++ b/models/cxr_image_synthesis_latent_diffusion_model/docs/README.md @@ -1,6 +1,6 @@ # Description -A diffusion model to synthetise X-Ray images based on radiological report impressions. +A diffusion model to synthetise X-Ray images based on radiological report impressions. # Model Overview This model is trained from scratch using the Latent Diffusion Model architecture [1] and is used for the synthesis of @@ -26,7 +26,7 @@ transformers package (https://github.com/huggingface/transformers) (pretrained m "stabilityai/stable-diffusion-2-1-base") and then encoded using CLIPTextModel from the same package and pretrained model. -# Examples of inference +# Examples of inference Here we included a few examples of commands to sample images from the model and save them as .jpg files. The available arguments for this task are: "--prompt" (str) text prompt to condition the model on; "--guidance_scale" (float), the @@ -54,7 +54,7 @@ $ python -m monai.bundle run save_jpg --config_file configs/inference.json --pro ## Using a new version of the model If you want to use the checkpoints from a newly fine-tuned model, you need to set parameter load_old to 0 when you run inference, -to avoid the function load_old_state_dict being called instead of load_state_dict to be called, currently default, as it is +to avoid the function load_old_state_dict being called instead of load_state_dict to be called, currently default, as it is required to load the checkpoint from the original GenerativeModels repository. ```shell From 315276b6c5690a3eee91839828bedc42e659e957 Mon Sep 17 00:00:00 2001 From: Virginia Date: Thu, 12 Dec 2024 09:45:06 +0000 Subject: [PATCH 4/6] Modification of metadata to remove generative package requirement, no longer necessary. On inference, modification of the entry point from save_jpg to run to allow for run to be called alone, and truncation of loading statements which are too long. Modification of the README to include command example changes. --- .../configs/inference.json | 8 +++++--- .../configs/metadata.json | 3 +-- .../docs/README.md | 10 +++++----- 3 files changed, 11 insertions(+), 10 deletions(-) diff --git a/models/cxr_image_synthesis_latent_diffusion_model/configs/inference.json b/models/cxr_image_synthesis_latent_diffusion_model/configs/inference.json index a45d0ff3..6578e3ea 100644 --- a/models/cxr_image_synthesis_latent_diffusion_model/configs/inference.json +++ b/models/cxr_image_synthesis_latent_diffusion_model/configs/inference.json @@ -45,7 +45,8 @@ "with_decoder_nonlocal_attn": false }, "load_autoencoder_path": "$@model_dir + '/autoencoder.pth'", - "load_autoencoder": "$@autoencoder_def.load_old_state_dict(torch.load(@load_autoencoder_path)) if bool(@load_old) else @autoencoder_def.load_state_dict(torch.load(@load_autoencoder_path))", + "load_autoencoder_func": "$@autoencoder_def.load_old_state_dict if bool(@load_old) else @autoencoder_def.load_state_dict", + "load_autoencoder": "$@load_autoencoder_func(torch.load(@load_autoencoder_path))", "autoencoder": "$@autoencoder_def.to(@device)", "diffusion_def": { "_target_": "monai.networks.nets.DiffusionModelUNet", @@ -76,7 +77,8 @@ "cross_attention_dim": 1024 }, "load_diffusion_path": "$@model_dir + '/diffusion_model.pth'", - "load_diffusion": "$@diffusion_def.load_old_state_dict(torch.load(@load_diffusion_path)) if bool(@load_old) else @diffusion_def.load_state_dict(torch.load(@load_diffusion_path))", + "load_diffusion_func": "$@diffusion_def.load_old_state_dict if bool(@load_old) else @diffusion_def.load_state_dict", + "load_diffusion": "$@load_diffusion_func(torch.load(@load_diffusion_path))", "diffusion": "$@diffusion_def.to(@device)", "scheduler": { "_target_": "monai.networks.schedulers.DDIMScheduler", @@ -103,6 +105,6 @@ "_requires_": "@create_output_dir", "output_dir": "@output_dir" }, - "save_jpg": "$@saver.save(@sample, @out_file)", + "run": "$@saver.save(@sample, @out_file)", "save": "$torch.save(@sample, @output_dir + '/' + @out_file + '.pt')" } diff --git a/models/cxr_image_synthesis_latent_diffusion_model/configs/metadata.json b/models/cxr_image_synthesis_latent_diffusion_model/configs/metadata.json index 020005e3..5c9f6596 100644 --- a/models/cxr_image_synthesis_latent_diffusion_model/configs/metadata.json +++ b/models/cxr_image_synthesis_latent_diffusion_model/configs/metadata.json @@ -9,7 +9,6 @@ "numpy_version": "1.22.4", "optional_packages_version": { "nibabel": "4.0.1", - "generative": "0.1.0", "transformers": "4.26.1" }, "task": "Chest X-ray image synthesis", @@ -26,7 +25,7 @@ "format": "magnitude", "modality": "CXR", "num_channels": 3, - "spatial_shape": [ + "spatial_shape": [77, 64, 64 ], diff --git a/models/cxr_image_synthesis_latent_diffusion_model/docs/README.md b/models/cxr_image_synthesis_latent_diffusion_model/docs/README.md index ac87910e..c0d90a0a 100644 --- a/models/cxr_image_synthesis_latent_diffusion_model/docs/README.md +++ b/models/cxr_image_synthesis_latent_diffusion_model/docs/README.md @@ -36,19 +36,19 @@ the image sticks to a given text input (the common range is between 1-21). Examples: ```shell -$ python -m monai.bundle run save_jpg --config_file configs/inference.json --prompt "Big right-sided pleural effusion" --guidance_scale 7.0 +$ python -m monai.bundle run --config_file configs/inference.json --prompt "Big right-sided pleural effusion" --guidance_scale 7.0 ``` ```shell -$ python -m monai.bundle run save_jpg --config_file configs/inference.json --prompt "Small right-sided pleural effusion" --guidance_scale 7.0 +$ python -m monai.bundle run --config_file configs/inference.json --prompt "Small right-sided pleural effusion" --guidance_scale 7.0 ``` ```shell -$ python -m monai.bundle run save_jpg --config_file configs/inference.json --prompt "Bilateral pleural effusion" --guidance_scale 7.0 +$ python -m monai.bundle run --config_file configs/inference.json --prompt "Bilateral pleural effusion" --guidance_scale 7.0 ``` ```shell -$ python -m monai.bundle run save_jpg --config_file configs/inference.json --prompt "Cardiomegaly" --guidance_scale 7.0 +$ python -m monai.bundle run --config_file configs/inference.json --prompt "Cardiomegaly" --guidance_scale 7.0 ``` ## Using a new version of the model @@ -58,7 +58,7 @@ to avoid the function load_old_state_dict being called instead of load_state_dic required to load the checkpoint from the original GenerativeModels repository. ```shell -$ python -m monai.bundle run save_jpg --config_file configs/inference.json --prompt "Pleural effusion." --guidance_scale 7.0 --load_old 0 +$ python -m monai.bundle run --config_file configs/inference.json --prompt "Pleural effusion." --guidance_scale 7.0 --load_old 0 ``` ## References From 4ec50d2ab0c92bd9b9e83d53ed869696cdf5c12d Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Thu, 12 Dec 2024 09:49:24 +0000 Subject: [PATCH 5/6] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- .../configs/metadata.json | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/models/cxr_image_synthesis_latent_diffusion_model/configs/metadata.json b/models/cxr_image_synthesis_latent_diffusion_model/configs/metadata.json index 5c9f6596..c257053f 100644 --- a/models/cxr_image_synthesis_latent_diffusion_model/configs/metadata.json +++ b/models/cxr_image_synthesis_latent_diffusion_model/configs/metadata.json @@ -25,7 +25,8 @@ "format": "magnitude", "modality": "CXR", "num_channels": 3, - "spatial_shape": [77, + "spatial_shape": [ + 77, 64, 64 ], From 13da7b1d70b5497738730633b5f4a256a1151112 Mon Sep 17 00:00:00 2001 From: Virginia Date: Tue, 17 Dec 2024 08:44:26 +0000 Subject: [PATCH 6/6] Added hash values and types to large_files.yml. For metadata, adjusted the versions, setting current to Initial Release. I also removed nibabel from the optional package requirements as this CXR produces JPG and does not deal with nifti files. --- .../configs/metadata.json | 11 +++++------ .../large_files.yml | 8 ++++---- 2 files changed, 9 insertions(+), 10 deletions(-) diff --git a/models/cxr_image_synthesis_latent_diffusion_model/configs/metadata.json b/models/cxr_image_synthesis_latent_diffusion_model/configs/metadata.json index 5c9f6596..28b274cf 100644 --- a/models/cxr_image_synthesis_latent_diffusion_model/configs/metadata.json +++ b/models/cxr_image_synthesis_latent_diffusion_model/configs/metadata.json @@ -2,14 +2,13 @@ "schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_20220324.json", "version": "1.0.0", "changelog": { - "0.2": "Flipped images fixed" + "1.0.0": "Initial release" }, - "monai_version": "1.1.0", - "pytorch_version": "1.13.0", - "numpy_version": "1.22.4", + "monai_version": "1.4.0", + "pytorch_version": "2.5.1", + "numpy_version": "1.26.4", "optional_packages_version": { - "nibabel": "4.0.1", - "transformers": "4.26.1" + "transformers": "4.46.3" }, "task": "Chest X-ray image synthesis", "description": "A generative model for creating high-resolution chest X-ray based on MIMIC dataset", diff --git a/models/cxr_image_synthesis_latent_diffusion_model/large_files.yml b/models/cxr_image_synthesis_latent_diffusion_model/large_files.yml index 3198186b..673824cb 100644 --- a/models/cxr_image_synthesis_latent_diffusion_model/large_files.yml +++ b/models/cxr_image_synthesis_latent_diffusion_model/large_files.yml @@ -1,9 +1,9 @@ large_files: - path: "models/autoencoder.pth" url: "https://drive.google.com/uc?export=download&id=1paDN1m-Q_Oy8d_BanPkRTi3RlNB_Sv_h" - hash_val: "" - hash_type: "" + hash_val: "7f579cb789597db7bb5de1488f54bc6c" + hash_type: "md5" - path: "models/diffusion_model.pth" url: "https://drive.google.com/uc?export=download&id=1CjcmiPu5_QWr-f7wDJsXrCCcVeczneGT" - hash_val: "" - hash_type: "" + hash_val: "c3fd4c8e38cd1d7250a8903cca935823" + hash_type: "md5"