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.github/ISSUE_TEMPLATE/feature_request.md

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+---
+name: Feature request
+about: 새로운 기능을 추가할 때 사용하는 템플릿
+title: "[FEAT] "
+labels: ''
+assignees: 'username'
+
+---
+## Background
+- 
+
+## To do
+- [ ]

.github/PULL_REQUEST_TEMPLATE.md

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+## PR Type
+- [ ] 기능 추가
+- [ ] 기능 삭제
+- [ ] 버그 수정
+- [ ] 의존성, 환경 변수, 빌드 관련 코드 업데이트
+
+
+## Change Log
+- 
+
+## To Reviewer
+- 
+
+## Issue Tags
+- Closed: #
+- See also: #

.gitignore

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+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+env/
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+
+# 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/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+.hypothesis/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# pyenv
+.python-version
+
+# celery beat schedule file
+celerybeat-schedule
+
+# SageMath parsed files
+*.sage.py
+
+# dotenv
+.env
+
+# virtualenv
+.venv
+venv/
+ENV/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+
+# input data, saved log, checkpoints
+data/
+input/
+saved/
+datasets/
+
+# editor, os cache directory
+.vscode/
+.idea/
+__MACOSX/
+
+wandb/
+result/

.pre-commit-config.yaml

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+# See https://pre-commit.com for more information
+# See https://pre-commit.com/hooks.html for more hooks
+repos:
+-   repo: https://github.com/pre-commit/pre-commit-hooks
+    rev: v4.5.0
+    hooks:
+    -   id: trailing-whitespace
+    -   id: check-yaml
+    -   id: check-json
+
+-   repo: https://github.com/psf/black
+    rev: 24.1.1
+    hooks:
+    -   id: black
+        args: ["-l", "79"]
+        name: black
+        description: "Black: The uncompromising Python code formatter"
+        entry: black
+        language: python
+        minimum_pre_commit_version: 2.9.2
+        require_serial: true
+        types_or: [python, pyi]
+
+-   repo: https://github.com/charliermarsh/ruff-pre-commit
+    rev: 'v0.1.14'
+    hooks:
+    -   id: ruff
+        args: [--ignore, F403]

EDA/gradcam.py

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+import warnings
+warnings.filterwarnings('ignore')
+warnings.simplefilter('ignore')
+
+import os
+import sys
+import torch
+import numpy as np
+import streamlit as st
+from PIL import Image
+
+from pytorch_grad_cam import GradCAM
+from pytorch_grad_cam.utils.image import show_cam_on_image
+
+sys.path.append(os.path.dirname(os.path.abspath(os.path.dirname(__file__))))
+from util import CLASSES, CLASS2IND
+from model import Unet, Linknet, FPN, PSPNet, PAN, FCN_ResNet50, FCN_ResNet101
+
+
+IMAGE_ROOT = "/data/ephemeral/home/datasets/test/DCM"
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+
+
+class SemanticSegmentationTarget:
+    def __init__(self, category, mask):
+        self.category = category
+        self.mask = torch.from_numpy(mask)
+        self.mask = self.mask.to(device)
+
+    def __call__(self, model_output):
+        return (model_output[self.category, :, : ] * self.mask).sum()
+
+
+def model_load(model_name, model_path):
+    if model_path.endswith('.pt'):
+        model = torch.load(model_path)
+    elif model_path.endswith('.pth'):
+        model = model_name
+        model_path = torch.load(model_path)
+        model = model.load_state_dict(model_path)
+    else:
+        st.warning("잘못된 확장자명이 입력되었습니다. .pt 또는 .pth 확장자를 사용해 주세요.")
+        model = None
+
+    return model
+
+
+def gradcam(model, target_layers, index, image_path, hand):
+    path = os.path.join(image_path, hand)
+
+    image = Image.open(path).convert('RGB')
+    image = image.resize((512,512))
+    image = np.array(image)
+
+    rgb_img = np.float32(image) / 255
+
+    img = rgb_img.transpose(2, 0, 1)  
+    img = torch.from_numpy(img).float()
+    img = torch.Tensor(img)
+    img = img.unsqueeze(0)
+
+    model = model.to(device)
+    input_tensor = img.to(device)
+
+    output = model(input_tensor)
+
+    normalized_masks = torch.nn.functional.softmax(output, dim=1).cpu() 
+    mask = normalized_masks[0, :, :, :].argmax(axis=0).detach().cpu().numpy() 
+    mask_float = np.float32(mask==index)
+
+    target = [SemanticSegmentationTarget(index, mask_float)]
+
+    with GradCAM(model=model,
+                target_layers=target_layers,) as cam:
+        grayscale_cam = cam(input_tensor=input_tensor, targets=target)[0,:]
+        cam_image = show_cam_on_image(rgb_img, grayscale_cam, use_rgb=True)
+
+    return cam_image
+
+
+def main():
+    st.set_page_config(
+        page_title = "GradCAM", 
+        page_icon="📷", 
+        layout = "wide", 
+    )
+
+    st.title("˙✧˖°📷 ༘ ⋆｡°")
+    st.markdown("<hr style='margin-top: 0; margin-bottom: 0; height: 1px; border: 1px solid #635985;'><br>", True)
+
+    images = {
+        os.path.relpath(os.path.join(root, fname), start=IMAGE_ROOT)
+        for root, _dirs, files in os.walk(IMAGE_ROOT)
+        for fname in files
+        if os.path.splitext(fname)[1].lower() == ".png"
+    }
+
+    title = []
+    for i, im in enumerate(images):
+        title.append(im[:5])
+    title = list(set(title))
+    title = sorted(title)
+
+    model_name = Unet
+    model_path = '/data/ephemeral/home/save_dir/resnet34_unet_best_model_start100.pt'
+
+    model = model_load(model_name, model_path)
+    model = model.eval()
+
+    target_layers = [model.decoder.blocks[4].conv2]
+
+    img_name = st.selectbox("Image", title)
+    category = st.multiselect("Classes", CLASSES, default=CLASSES[0])    
+
+    right_cam, left_cam = [], []
+    for cate in category:
+        index = CLASS2IND[cate]
+        image_path = os.path.join(IMAGE_ROOT, img_name)
+        image_file = os.listdir(image_path)
+
+        right = image_file[0]
+        left = image_file[1]
+
+        right = gradcam(model, target_layers, index, image_path, right)
+        left = gradcam(model, target_layers, index, image_path, left)
+
+        right_cam.append(right)
+        left_cam.append(left)
+
+
+    r_combined_cam = None
+    l_combined_cam = None
+
+    for cam in right_cam:
+        if r_combined_cam is None:
+            r_combined_cam = cam
+        else:
+            r_combined_cam = np.maximum(r_combined_cam, cam)
+
+    for cam in left_cam:
+        if l_combined_cam is None:
+            l_combined_cam = cam
+        else:
+            l_combined_cam = np.maximum(l_combined_cam, cam)
+
+    show_image_R = Image.fromarray(r_combined_cam)
+    show_image_L = Image.fromarray(l_combined_cam)
+
+
+    col1, col2 = st.columns(2)
+
+    with col1:
+        st.header("Right")
+        st.image(show_image_R)
+
+    with col2:
+        st.header("Left")
+        st.image(show_image_L)
+
+
+if __name__ == "__main__":
+    main()

EDA/pisiform.txt

@@ -0,0 +1,31 @@
+ID001/image1661130828152_R.png 0.658682644367218
+ID001/image1661130891365_L.png 0.8267679214477539
+ID010/image1661145563354.png 0.8990980982780457
+ID015/image1661216971933.png 0.767647922039032
+ID015/image1661216998230.png 0.7194860577583313
+ID021/image1661303624585.png 0.8322030901908875
+ID027/image1661305195948.png 0.814268171787262
+ID032/image1661317566170.png 0.8664231896400452
+ID036/image1661318659827.png 0.7022705674171448
+ID036/image1661318687383.png 0.7908452153205872
+ID057/image1661391973543.png 0.865178644657135
+ID075/image1661736898823.png 0.7843137383460999
+ID077/image1661737137803.png 0.8726937174797058
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+ID302/image1664241064255.png 0.8493593335151672
+ID309/image1664241485928.png 0.3928753137588501
+ID331/image1664847291816.png 0.8689588308334351
+ID344/image1664932490676.png 0.828208863735199
+ID374/image1665452614591.png 0.668241560459137
+ID397/image1665538903963.png 0.8486701250076294
+ID402/image1665539357117.png 0.8608115315437317
+ID402/image1665539372545.png 0.8133237361907959
+ID409/image1665540974169.png 0.8973684310913086
+ID439/image1666141941646.png 0.8776015639305115
+ID445/image1666144399306.png 0.8360981941223145
+ID462/image1666575444051.png 0.8434149026870728
+ID518/image1666749056245.png 0.8682605624198914
+ID518/image1666749083578.png 0.8988138437271118
+ID539/image1667266283922.png 0.8451685905456543