Change litemedsam installation procedure

Author: uw0s

README

@@ -13,7 +13,5 @@ cd $HOME/github.com/valab-certh/meddisc
 cd python/ && make clean check all && cd ..
 
 # Staging
-printf 'USERNAME=user\n' >> python/.env
-printf 'PASSWORD=pass\n' >> python/.env
 cd python/ && make STAGING=1
 

python/Dockerfile

@@ -1,6 +1,5 @@
 FROM python:3.12-slim
-RUN apt-get update && apt-get install git libgl1-mesa-glx libglib2.0-0 libsm6 libxext6 libxrender1 libfontconfig1 libice6 -y
+RUN apt-get update && apt-get install libgl1-mesa-glx libglib2.0-0 -y
 WORKDIR /usr/src/app
 COPY pyproject.toml .
-RUN python3 -m pip install --upgrade pip && python3 -m pip install .[dev]
-RUN git clone -b LiteMedSAM https://github.com/bowang-lab/MedSAM/ /usr/src/MedSAM && cd /usr/src/MedSAM/ && python3 -m pip install -e .
+RUN python3 -m pip install --upgrade pip && python3 -m pip install .[dev]

python/main.py

@@ -25,6 +25,7 @@
 import pandas as pd
 import pydicom
 import pytest
+import requests
 import torch
 from fastapi import Body, FastAPI, Request, UploadFile, status
 from fastapi.responses import HTMLResponse
@@ -35,14 +36,15 @@
 from pydantic import BaseModel
 from pydicom.errors import InvalidDicomError
 from segment_anything.modeling import MaskDecoder, PromptEncoder, TwoWayTransformer
-from tiny_vit_sam import TinyViT
 from torch import nn
 from torch.nn import functional
 from uvicorn import run
 
 if TYPE_CHECKING:
     from numpy.typing import NDArray
 
+    from tmp.tiny_vit_sam import TinyViT
+
 
 class UserOptionsClass(BaseModel):
     skip_deidentification: bool
@@ -275,6 +277,8 @@ def postprocess_masks(
 
 @lru_cache(maxsize=1)
 def load_model() -> MedsamLite:
+    from tmp.tiny_vit_sam import TinyViT
+
     medsam_lite_image_encoder = TinyViT(
         img_size=256,
         in_chans=3,
@@ -1482,8 +1486,16 @@ def meddisc() -> None:
     for directory in tmp_directories:
         directory.mkdir(parents=True, exist_ok=True)
     csv_path = Path("tmp/action-groups-dcm.csv")
+    vit_path = Path("tmp/tiny_vit_sam.py")
+    vit_url = "https://api.github.com/repos/bowang-lab/MedSAM/contents/tiny_vit_sam.py?ref=LiteMedSAM"
     if not csv_path.exists():
         generate_action_groups()
+    if not vit_path.exists():
+        response = requests.get(vit_url, timeout=10)
+        content = response.json()["content"]
+        file_content = base64.b64decode(content).decode("utf-8")
+        with vit_path.open("w") as f:
+            f.write(file_content)
     if os.getenv("STAGING"):
         if not Path("tmp/fullchain.pem").exists():
             subprocess.run(

python/pyproject.toml

@@ -4,14 +4,14 @@ dependencies = [
   "fastapi==0.110.0",
   "fire==0.6.0",
   "keras-ocr==0.9.3",
+  "litemedsam@https://api.github.com/repos/bowang-lab/MedSAM/tarball/LiteMedSAM",
   "lxml==5.2.0",
   "pydicom==2.4.4",
   "pylibjpeg-libjpeg==2.1.0",
   "pylibjpeg==2.0.0",
   "pytest==8.1.1",
-  "python-dotenv==1.0.1",
   "python-multipart==0.0.9",
-  "segment-anything@git+https://github.com/facebookresearch/segment-anything.git@6fdee8f2727f4506cfbbe553e23b895e27956588",
+  "segment-anything@https://api.github.com/repos/facebookresearch/segment-anything/tarball/main",
   "tensorflow==2.16.1",
   "torch@https://download.pytorch.org/whl/cpu/torch-2.2.1%2Bcpu-cp312-cp312-linux_x86_64.whl",
   "torchvision@https://download.pytorch.org/whl/cpu/torchvision-0.17.1%2Bcpu-cp312-cp312-linux_x86_64.whl",