Merge pull request #317 from AIM-Harvard/patch0001

Patch0001
AIM-Harvard · Feb 6, 2025 · db64439 · db64439
2 parents 860b90b + a7ae531
commit db64439
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Showing 8 changed files with 571 additions and 130 deletions.
diff --git a/Makefile b/Makefile
@@ -1,6 +1,7 @@
 #* Variables
 SHELL := /usr/bin/env bash
-PYTHON := python
+PYTHON := python3
+python := python3
 PYTHONPATH := `pwd`
 
 #* Docker variables

diff --git a/docs/replication-guide/baselines.md b/docs/replication-guide/baselines.md
@@ -10,7 +10,7 @@ By default, we configure this for Task 1. You can adapt this for Task 2 and Task
 
 You can start training by running this in the root code folder,
 ```bash
-lighter fit --config_file ./experiments/baselines/supervised_training/supervised_random_init.yaml
+lighter fit --config_file=./experiments/baselines/supervised_training/supervised_random_init.yaml
 ```
 
 ## Transfer learning
@@ -20,7 +20,7 @@ This baseline is only used for Task 2 and Task 3 as we use the random init basel
 
 You can start training by running this in the root code folder,
 ```bash
-lighter fit --config_file ./experiments/baselines/supervised_training/supervised_finetune.yaml
+lighter fit --config_file=./experiments/baselines/supervised_training/supervised_finetune.yaml
 ```
 
 ## Med3D / MedicalNet
@@ -31,7 +31,7 @@ We have provided re-implementations of Med3D to fit into our YAML workflows at `
 
 You can start training by running this in the root code folder,
 ```bash
-lighter fit --config_file ./experiments/baselines/med3d/finetune.yaml
+lighter fit --config_file=./experiments/baselines/med3d/finetune.yaml
 ```
 
 ## Models Genesis
@@ -42,5 +42,5 @@ We have provided re-implementations of Models Genesis to fit into our YAML workf
 
 You can start training by running this in the root code folder,
 ```bash
-lighter fit --config_file ./experiments/baselines/models_genesis/finetune.yaml
+lighter fit --config_file=./experiments/baselines/models_genesis/finetune.yaml
 ```
diff --git a/docs/replication-guide/fm_adaptation.md b/docs/replication-guide/fm_adaptation.md
@@ -11,7 +11,7 @@ By default, we configure this for Task 1. You can adapt this for Task 2 and Task
 
 You can start training by running this in the root code folder,
 ```bash
-lighter fit --config_file ./experiments/adaptation/fmcib_finetune.yaml
+lighter fit --config_file=./experiments/adaptation/fmcib_finetune.yaml
 ```
 
 ## Adaptation through linear evaluation

diff --git a/docs/replication-guide/inference.md b/docs/replication-guide/inference.md
@@ -6,7 +6,7 @@ In this section, we detail how features (from the FM and pre-trained models) and
 
 In order to extract features from our models, you can use the following, (at root folder location)
 ```bash
-lighter predict --config_file ./experiments/inference/extract_features.yaml
+lighter predict --config_file=./experiments/inference/extract_features.yaml
 ```
 
 !!! note
@@ -33,7 +33,7 @@ This will pull all the models from hugging face. Following this you can use any
 These can be run using (at root folder location)
 
 ```bash
-lighter predict --config_file ./experiments/inference/get_predictions.yaml
+lighter predict --config_file=./experiments/inference/get_predictions.yaml
 ```
 As with the previous YAMLS, please follow the 'Note:' tags to place appropriate data paths and change relevant parameters. This YAML is to be used if you want to get target predictions from the models.
 

diff --git a/docs/replication-guide/reproduce_fm.md b/docs/replication-guide/reproduce_fm.md
@@ -51,5 +51,5 @@ Now you can start training by running this in the root code folder,
 
 
 ```bash
-lighter fit --config_file ./experiments/pretraining/fmcib_pretrain.yaml
+lighter fit --config_file=./experiments/pretraining/fmcib_pretrain.yaml
 ```
diff --git a/fmcib/utils/idc_helper.py b/fmcib/utils/idc_helper.py
@@ -215,14 +215,14 @@ def process_series_dir(series_dir: Path):
 
     elif len(seg_files) != 0:
         dcmseg2nii(str(seg_files[0]), str(series_dir), tag="GTV-")
-        
+
         # Build the main image NIfTI
         try:
             series_id = str(list(series_dir.glob("CT*.dcm"))[0]).split("_")[-2]
         except IndexError:
             logger.warning(f"No 'CT*.dcm' file found under {series_dir}. Skipping.")
             return None
-        
+
         dicom_image = DcmInputAdapter().ingest(str(series_dir), series_id=series_id)
         nii_output_adapter = NiiOutputAdapter()
         nii_output_adapter.write(dicom_image, f"{series_dir}/image", gzip=True)
@@ -231,7 +231,7 @@ def process_series_dir(series_dir: Path):
         logger.warning(f"No RTSTRUCT or SEG file found in {series_dir}. Skipping.")
         return None
 
-    # Read the image (generated above) 
+    # Read the image (generated above)
     image_path = series_dir / "image.nii.gz"
     if not image_path.exists():
         logger.warning(f"No image file found at {image_path}. Skipping.")

diff --git a/poetry.lock b/poetry.lock
diff --git a/pyproject.toml b/pyproject.toml
@@ -51,9 +51,9 @@ pydantic = "1.10.13"
 lightly = "1.4.19"
 werkzeug = "^3.0.1"
 urllib3 = ">=2.2.2"
-aiohttp = "^3.9.1"
+aiohttp = "^3.11.12"
 pip = "^24.0"
-tornado = ">=6.4.1"
+tornado = "^6.4.2"
 wandb = "^0.16.3"
 mpmath = "1.3.0"
 zipp = ">=3.19.1"
@@ -64,6 +64,9 @@ scikit-learn = ">=1.5.0"
 requests = ">=2.32.2"
 mkdocs-material = ">=9.5.32"
 certifi = ">=2024.07.04"
+sqlalchemy = "^2.0.37"
+gunicorn = "^23.0.0"
+jinja2 = "^3.1.5"
 
 [tool.poetry.group.dev.dependencies]
 black = "^24.4.2"
-Original file line number
+Diff line change
@@ Expand Up @@
     ```bash
-    lighter fit --config_file ./experiments/pretraining/fmcib_pretrain.yaml
+    lighter fit --config_file=./experiments/pretraining/fmcib_pretrain.yaml
     ```