from sklearn.externals import joblib import numpy as np from ipfml import image_processing from PIL import Image import sys, os, getopt import subprocess import time current_dirpath = os.getcwd() threshold_map_folder = "threshold_map" threshold_map_file_prefix = "treshold_map_" markdowns_folder = "models_info" zones = np.arange(16) def main(): if len(sys.argv) <= 1: print('Run with default parameters...') print('python save_model_result_in_md.py --interval "0,20" --model path/to/xxxx.joblib --mode ["svd", "svdn", "svdne"] --metric ["lab", "mscn"]') sys.exit(2) try: opts, args = getopt.getopt(sys.argv[1:], "ht:m:o:l", ["help=", "interval=", "model=", "mode=", "metric="]) except getopt.GetoptError: # print help information and exit: print('python save_model_result_in_md.py --interval "xx,xx" --model path/to/xxxx.joblib --mode ["svd", "svdn", "svdne"] --metric ["lab", "mscn"]') sys.exit(2) for o, a in opts: if o == "-h": print('python save_model_result_in_md.py --interval "xx,xx" --model path/to/xxxx.joblib --mode ["svd", "svdn", "svdne"] --metric ["lab", "mscn"]') sys.exit() elif o in ("-t", "--interval"): p_interval = list(map(int, a.split(','))) elif o in ("-m", "--model"): p_model_file = a elif o in ("-o", "--mode"): p_mode = a if p_mode != 'svdn' and p_mode != 'svdne' and p_mode != 'svd': assert False, "Mode not recognized" elif o in ("-me", "--metric"): p_metric = a else: assert False, "unhandled option" # call model and get global result in scenes begin, end = p_interval bash_cmd = "bash testModelByScene.sh '" + str(begin) + "' '" + str(end) + "' '" + p_model_file + "' '" + p_mode + "' '" + p_metric + "'" print(bash_cmd) ## call command ## p = subprocess.Popen(bash_cmd, stdout=subprocess.PIPE, shell=True) (output, err) = p.communicate() ## Wait for result ## p_status = p.wait() if not os.path.exists(markdowns_folder): os.makedirs(markdowns_folder) # get model name to construct model md_model_path = os.path.join(markdowns_folder, p_model_file.split('/')[-1].replace('.joblib', '.md')) with open(md_model_path, 'w') as f: f.write(output.decode("utf-8")) # read each threshold_map information if exists model_map_info_path = os.path.join(threshold_map_folder, p_model_file.replace('saved_models/', '')) if not os.path.exists(model_map_info_path): f.write('\n\n No threshold map information') else: maps_files = os.listdir(model_map_info_path) # get all map information for t_map_file in maps_files: file_path = os.path.join(model_map_info_path, t_map_file) with open(file_path, 'r') as map_file: title_scene = t_map_file.replace(threshold_map_file_prefix, '') f.write('\n\n## ' + title_scene + '\n') content = map_file.readlines() # getting each map line information for line in content: f.write(line) f.close() if __name__== "__main__": main()