add gitignore, add option to not show heatmap

.gitignore

@@ -0,0 +1,170 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# UV
+#   Similar to Pipfile.lock, it is generally recommended to include uv.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#uv.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/latest/usage/project/#working-with-version-control
+.pdm.toml
+.pdm-python
+.pdm-build/
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/
+
+.gradio

app.py

@@ -70,7 +70,7 @@ greulich_and_pyle_ages = {k: np.asarray(v) for k, v in greulich_and_pyle_ages.it
 model_grad_cam = ModelForGradCAM(model_list[0])
 target_layers = [model_grad_cam.model.backbone.stages[-1]]
 
-def predict_bone_age(Radiograph, Sex):
+def predict_bone_age(Radiograph, Sex, Heatmap):
     x0 = rearrange(Radiograph, "h w -> h w 1")
     x = cfg_crop.val_transforms(image=x0)["image"]
     x = torch.from_numpy(x)
@@ -115,23 +115,28 @@ def predict_bone_age(Radiograph, Sex):
     closest1 = convert_bone_age_to_string(closest1)
     closest2 = convert_bone_age_to_string(closest2)
 
-    targets = [ClassifierOutputTarget(round(bone_age))]
-    with GradCAM(model=model_grad_cam, target_layers=target_layers) as cam:
-        grayscale_cam = cam(input_tensor=x.to(device).float(), targets=targets, eigen_smooth=True)
-    
-    heatmap = cv2.applyColorMap((grayscale_cam[0] * 255).astype("uint8"), cv2.COLORMAP_JET)
-    image = cv2.cvtColor(x[0, 0].cpu().numpy().astype("uint8"), cv2.COLOR_GRAY2RGB)
-    image_weight = 0.6
-    grad_cam_image = (1 - image_weight) * heatmap[..., ::-1] + image_weight * image
-    grad_cam_image = grad_cam_image.astype("uint8")
+    if Heatmap:
+        targets = [ClassifierOutputTarget(round(bone_age))]
+        with GradCAM(model=model_grad_cam, target_layers=target_layers) as cam:
+            grayscale_cam = cam(input_tensor=x.to(device).float(), targets=targets, eigen_smooth=True)
+
+        heatmap = cv2.applyColorMap((grayscale_cam[0] * 255).astype("uint8"), cv2.COLORMAP_JET)
+        image = cv2.cvtColor(x[0, 0].cpu().numpy().astype("uint8"), cv2.COLOR_GRAY2RGB)
+        image_weight = 0.6
+        grad_cam_image = (1 - image_weight) * heatmap[..., ::-1] + image_weight * image
+        grad_cam_image = grad_cam_image.astype("uint8")
+    else:
+        # if no heatmap desired, just show image
+        grad_cam_image = cv2.cvtColor(x[0, 0].cpu().numpy().astype("uint8"), cv2.COLOR_GRAY2RGB)
 
     return f"Predicted bone age: {bone_age_str}\n\nThe closest Greulich & Pyle bone ages are:\n  1) {closest1}\n  2) {closest2}", grad_cam_image
 
 
 image = gr.Image(image_mode="L")
 sex = gr.Radio(["Male", "Female"], type="index")
+generate_heatmap = gr.Radio(["No", "Yes"], type="index")
 textbox = gr.Textbox(show_label=True, label="Result")
-grad_cam_image = gr.Image(image_mode="RGB", label="Heatmap")
+grad_cam_image = gr.Image(image_mode="RGB", label="Heatmap / Image")
 
 with gr.Blocks() as demo:
     gr.Markdown(
@@ -144,6 +149,9 @@ with gr.Blocks() as demo:
     The model achieves a mean absolute error of 4.26 months on the original test set comprising 200 multi-annotated hand radiographs, 
     which is competitive with [top solutions](https://pubs.rsna.org/doi/10.1148/radiol.2018180736) from the original challenge.
 
+    There is also an option to output a heatmap over the radiograph to show regions where the model is focusing on
+    to make its prediction. However, this takes extra computation and will increase the runtime.
+
     This model is for demonstration purposes only and has NOT been approved by any regulatory agency for clinical use. The user assumes
     any and all responsibility regarding their own use of this model and its outputs. Do NOT upload any images containing protected
     health information, as this demonstration is not compliant with patient privacy laws.
@@ -155,13 +163,14 @@ with gr.Blocks() as demo:
     )
     gr.Interface(
         fn=predict_bone_age,
-        inputs=[image, sex],
+        inputs=[image, sex, generate_heatmap],
         outputs=[textbox, grad_cam_image],
         examples=[
-            ["examples/2639.png", "Female"],
-            ["examples/10043.png", "Female"],
-            ["examples/8888.png", "Female"],
+            ["examples/2639.png", "Female", "Yes"],
+            ["examples/10043.png", "Female", "No"],
+            ["examples/8888.png", "Female", "Yes"],
         ],
+        cache_examples=False
     )
 
 if __name__ == "__main__":