Download models in Dockerfile + revert request changes

Dockerfile

@@ -22,6 +22,10 @@ WORKDIR /code
 RUN apt-get update -y
 RUN apt install git --fix-missing -y
 
+# Download pretrained parenchyma model
+RUN wget "https://github.com/andreped/livermask/releases/download/trained-models-v1/model.h5"
+COPY ./model.h5 /code/model.h5
+
 # install dependencies
 COPY ./demo/requirements.txt /code/demo/requirements.txt
 RUN python3.7 -m pip install --no-cache-dir --upgrade -r /code/demo/requirements.txt
@@ -29,10 +33,6 @@ RUN python3.7 -m pip install --no-cache-dir --upgrade -r /code/demo/requirements
 # resolve issue with tf==2.4 and gradio dependency collision issue
 RUN python3.7 -m pip install --force-reinstall typing_extensions==4.0.0
 
-# allow container to access outside world
-RUN apt-get update && apt install iptables -y
-RUN sysctl net.ipv4.conf.all.forwarding=1
-
 # Set up a new user named "user" with user ID 1000
 RUN useradd -m -u 1000 user
 

demo/app.py

@@ -29,7 +29,7 @@ def nifti_to_glb(path):
 def run_model(input_path):
     from livermask.utils.run import run_analysis
     
-    run_analysis(cpu=False, extension='.nii', path=input_path, output='prediction', verbose=True, vessels=False)
+    run_analysis(cpu=False, extension='.nii', path=input_path, output='prediction', verbose=True, vessels=False, name="./model.h5")
     
     #cmd_docker = ["python3", "-m", "livermask.livermask", "--input", input_path, "--output", "prediction", "--verbose"]
     #sp.check_call(cmd_docker, shell=True)  # @FIXME: shell=True here is not optimal -> starts a shell after calling script

livermask/utils/fetch.py

@@ -12,11 +12,7 @@ def download(url, destination_file):
         mtime = os.path.getmtime(destination_file)
         headers["if-modified-since"] = formatdate(mtime, usegmt=True)
 
-    # relevant for docker
-    session = requests.Session()
-    session.trust_env = False
-
-    response = session.get(url, headers=headers, stream=True)
+    response = requests.get(url, headers=headers, stream=True)
     response.raise_for_status()
 
     if response.status_code == requests.codes.not_modified:

livermask/utils/run.py

@@ -24,22 +24,24 @@ import logging as log
 from .utils import get_model, get_vessel_model
 
 
-def run_analysis(path, output, cpu, verbose, vessels, extension):
+def run_analysis(path, output, cpu, verbose, vessels, extension, name=None, name_vessel=None):
     # fix paths (necessary if called as a package and not CLI)
     path = path.replace("\\", "/")
     output = output.replace("\\", "/")
 
     # enable verbose or not
     log = verboseHandler(verbose)
-
+    
+    # if model names are not provided, download them (necessary for docker,
+    # where we cannot perform HTTP requests from inside container)
     cwd = "/".join(os.path.realpath(__file__).replace("\\", "/").split("/")[:-1]) + "/"
-    name = cwd + "model.h5"
-    name_vessel = cwd + "model-hepatic_vessel.npz"
-
-    # get models
-    get_model(name)
-
-    if vessels:
+    log.info("Model names: " + str(name) + ", " + str(name_vessel))
+    if name is None:
+        name = cwd + "model.h5"
+        get_model(name)
+    
+    if vessels and name_vessel is None:
+        name_vessel = cwd + "model-hepatic_vessel.npz"
         get_vessel_model(name_vessel)
 
     if not os.path.isdir(path):
@@ -61,4 +63,4 @@ def run_analysis(path, output, cpu, verbose, vessels, extension):
                 # perform liver vessel segmentation
                 vessel_segmenter(curr, output, cpu, verbose, multiple_flag, pred, name_vessel, extension)
         else:
-            log.info("Unsuported file: " + curr)
+            log.info("Unsupported file: " + curr)