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valve_landmarks

monai
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katielink commited on
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1 Parent(s): e187296

README.md fix

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Files changed (3) hide show
  1. README.md +2 -2
  2. configs/metadata.json +2 -1
  3. docs/README.md +2 -2
README.md CHANGED
@@ -49,7 +49,7 @@ The dataset used for training unfortunately cannot be made public, however the t
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  The following command will train with the default NPZ filename `./valvelandmarks.npz`, assuming the current directory is the bundle directory:
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  ```sh
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- python -m monai.bundle run training --meta_file configs/metadata.json --config_file "['configs/train.json', 'configs/common.json']" \
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  --bundle_root . --dataset_file ./valvelandmarks.npz --output_dir /path/to/outputs
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  ```
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@@ -58,7 +58,7 @@ python -m monai.bundle run training --meta_file configs/metadata.json --config_f
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  The included `inference.json` script will run inference on a directory containing Nifti files whose images have shape `(256, 256, 1, N)` for `N` timesteps. For each image the output in the `output_dir` directory will be a npy file containing a result array of shape `(N, 2, 10)` storing the 10 coordinates for each `N` timesteps. Invoking this script can be done as follows, assuming the current directory is the bundle directory:
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  ```sh
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- python -m monai.bundle run evaluating --meta_file configs/metadata.json --config_file "['configs/inference.json', 'configs/common.json']" \
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  --bundle_root . --dataset_dir /path/to/data --output_dir /path/to/outputs
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  ```
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  The following command will train with the default NPZ filename `./valvelandmarks.npz`, assuming the current directory is the bundle directory:
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  ```sh
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+ python -m monai.bundle run training --meta_file configs/metadata.json --config_file configs/train.json \
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  --bundle_root . --dataset_file ./valvelandmarks.npz --output_dir /path/to/outputs
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  ```
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  The included `inference.json` script will run inference on a directory containing Nifti files whose images have shape `(256, 256, 1, N)` for `N` timesteps. For each image the output in the `output_dir` directory will be a npy file containing a result array of shape `(N, 2, 10)` storing the 10 coordinates for each `N` timesteps. Invoking this script can be done as follows, assuming the current directory is the bundle directory:
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  ```sh
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+ python -m monai.bundle run evaluating --meta_file configs/metadata.json --config_file configs/inference.json \
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  --bundle_root . --dataset_dir /path/to/data --output_dir /path/to/outputs
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  ```
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configs/metadata.json CHANGED
@@ -1,7 +1,8 @@
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  {
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  "schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_20220729.json",
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- "version": "0.4.2",
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  "changelog": {
 
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  "0.4.2": "add name tag",
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  "0.4.1": "modify dataset key name",
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  "0.4.0": "update license files",
 
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  {
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  "schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_20220729.json",
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+ "version": "0.4.3",
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  "changelog": {
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+ "0.4.3": "README.md fix",
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  "0.4.2": "add name tag",
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  "0.4.1": "modify dataset key name",
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  "0.4.0": "update license files",
docs/README.md CHANGED
@@ -42,7 +42,7 @@ The dataset used for training unfortunately cannot be made public, however the t
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  The following command will train with the default NPZ filename `./valvelandmarks.npz`, assuming the current directory is the bundle directory:
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  ```sh
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- python -m monai.bundle run training --meta_file configs/metadata.json --config_file "['configs/train.json', 'configs/common.json']" \
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  --bundle_root . --dataset_file ./valvelandmarks.npz --output_dir /path/to/outputs
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  ```
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@@ -51,7 +51,7 @@ python -m monai.bundle run training --meta_file configs/metadata.json --config_f
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  The included `inference.json` script will run inference on a directory containing Nifti files whose images have shape `(256, 256, 1, N)` for `N` timesteps. For each image the output in the `output_dir` directory will be a npy file containing a result array of shape `(N, 2, 10)` storing the 10 coordinates for each `N` timesteps. Invoking this script can be done as follows, assuming the current directory is the bundle directory:
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  ```sh
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- python -m monai.bundle run evaluating --meta_file configs/metadata.json --config_file "['configs/inference.json', 'configs/common.json']" \
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  --bundle_root . --dataset_dir /path/to/data --output_dir /path/to/outputs
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  ```
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42
  The following command will train with the default NPZ filename `./valvelandmarks.npz`, assuming the current directory is the bundle directory:
43
 
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  ```sh
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+ python -m monai.bundle run training --meta_file configs/metadata.json --config_file configs/train.json \
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  --bundle_root . --dataset_file ./valvelandmarks.npz --output_dir /path/to/outputs
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  ```
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  The included `inference.json` script will run inference on a directory containing Nifti files whose images have shape `(256, 256, 1, N)` for `N` timesteps. For each image the output in the `output_dir` directory will be a npy file containing a result array of shape `(N, 2, 10)` storing the 10 coordinates for each `N` timesteps. Invoking this script can be done as follows, assuming the current directory is the bundle directory:
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  ```sh
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+ python -m monai.bundle run evaluating --meta_file configs/metadata.json --config_file configs/inference.json \
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  --bundle_root . --dataset_dir /path/to/data --output_dir /path/to/outputs
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  ```
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