first commit

Scripts/Dockerfile

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+FROM ubuntu:20.04
+
+# Label
+LABEL org.opencontainers.image.title="fish cropping and trait morphology"
+LABEL org.opencontainers.image.authors=" T. Tabarin"
+LABEL org.opencontainers.image.source="https://github.com/hdr-bgnn/BGNN_Snakemake"
+
+# Install some basic utilities
+RUN apt-get update && apt-get install -y \
+    curl \
+    ca-certificates \
+    sudo \
+    git \
+    bzip2 \
+    libx11-6 \
+    wget \
+ && rm -rf /var/lib/apt/lists/*
+
+# Create a working directory
+RUN mkdir /app
+WORKDIR /app
+
+# Create a non-root user and switch to it
+RUN adduser --disabled-password --gecos '' --shell /bin/bash user \
+ && chown -R user:user /app
+RUN echo "user ALL=(ALL) NOPASSWD:ALL" > /etc/sudoers.d/90-user
+USER user
+
+# All users can use /home/user as their home directory
+ENV HOME=/home/user
+RUN chmod 777 /home/user
+
+# Set up the Conda environment
+ENV CONDA_AUTO_UPDATE_CONDA=false \
+    PATH=/home/user/miniconda/bin:$PATH
+COPY morphology_env.yml /app/environment.yml
+RUN curl -sLo ~/miniconda.sh https://repo.anaconda.com/miniconda/Miniconda3-py38_4.9.2-Linux-x86_64.sh \
+ && chmod +x ~/miniconda.sh \
+ && ~/miniconda.sh -b -p ~/miniconda \
+ && rm ~/miniconda.sh \
+ && conda env update -n base -f /app/environment.yml \
+ && rm /app/environment.yml \
+ && conda clean -ya
+
+WORKDIR /pipeline
+
+# Setup pipeline specific scripts
+ENV PATH="/pipeline/Morphology:${PATH}"
+ENV PATH="/pipeline/Crop:${PATH}"
+ENV PATH="/pipeline/Merge_files:${PATH}"
+ADD Crop_image/Crop_image_main.py /pipeline/Crop/Crop_image_main.py
+ADD Morphology/Traits_class.py /pipeline/Morphology/Traits_class.py
+ADD Morphology/Morphology_main.py /pipeline/Morphology/Morphology_main.py
+ADD Merge_files/Merge_files_main.py /pipeline/Merge_files/Merge_files_main.py
+
+# Set the default command to a usage statement
+CMD echo "Usage crop: Crop_image_main.py <input_image.jpg> <image_metadata.json> <image_cropped.png>\n"\
+"Usage Morphology: Morphology_main.py  <input_file> <measure.json> <landmark.json> <presence.json> <image_lm.png>\n"\
+"Usage Merge_file: Merge_files_main.py  <input_directory> <merge.csv> <merge.json>"

Scripts/Morphology_main.py

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+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Created on Tue May 24 09:21:33 2022
+
+@author: thibault
+"""
+import Traits_class as tc
+import json, sys
+
+def get_scale(metadata_file):
+
+    '''
+    extract the scale value from metadata file
+    '''
+
+    f = open(metadata_file)
+    data = json.load(f)
+    metadata_dict = list(data.values())[0]
+
+    if 'scale' in metadata_dict  :
+
+        scale = round(metadata_dict['scale'],3)
+        unit = metadata_dict['unit']
+    else:
+        scale =[None]
+        unit =[None]
+    return scale , unit
+
+
+def main(input_file, metadata_file, output_measure, output_landmark, output_presence, 
+         output_lm_image=None):
+
+    img_seg = tc.segmented_image(input_file)
+    measurement = img_seg.measurement
+    landmark = img_seg.landmark
+    presence_matrix = img_seg.presence_matrix
+
+    # Extract the scale from metadata file
+    # and add it to measurement dict
+    scale , unit = get_scale(metadata_file)
+    measurement['scale'] = scale
+    measurement['unit'] = unit                   
+
+    # Save the dictionnaries in json file
+    with open(output_measure, 'w') as f:
+        json.dump(measurement, f)    
+
+    with open(output_landmark, 'w') as f:
+        json.dump(landmark, f)
+
+    with open(output_presence, 'w') as f:
+        json.dump(presence_matrix, f)    
+
+    if output_lm_image:
+
+        img_landmark = img_seg.visualize_landmark()
+        img_landmark.save(output_lm_image)
+
+
+if __name__ == '__main__':
+
+    input_file = sys.argv[1]
+    metadata_file = sys.argv[2]
+    output_measure = sys.argv[3]
+    output_landmark = sys.argv[4]
+    output_presence = sys.argv[5]
+    output_lm_image = None
+
+
+    if len(sys.argv)==7:
+        output_lm_image = sys.argv[6]
+
+    main(input_file, metadata_file, output_measure, output_landmark, output_presence, 
+         output_lm_image=output_lm_image)