Security3 (#10944)

segment/train.py

@@ -19,6 +19,7 @@ import argparse
 import math
 import os
 import random
+import subprocess
 import sys
 import time
 from copy import deepcopy
@@ -597,7 +598,8 @@ def main(opt, callbacks=Callbacks()):
         # ei = [isinstance(x, (int, float)) for x in hyp.values()]  # evolvable indices
         evolve_yaml, evolve_csv = save_dir / 'hyp_evolve.yaml', save_dir / 'evolve.csv'
         if opt.bucket:
-            os.system(f'gsutil cp gs://{opt.bucket}/evolve.csv {evolve_csv}')  # download evolve.csv if exists
+            subprocess.run(
+                f'gsutil cp gs://{opt.bucket}/evolve.csv {evolve_csv}'.split())  # download evolve.csv if exists
 
         for _ in range(opt.evolve):  # generations to evolve
             if evolve_csv.exists():  # if evolve.csv exists: select best hyps and mutate

segment/val.py

@@ -23,6 +23,7 @@ Usage - formats:
 import argparse
 import json
 import os
+import subprocess
 import sys
 from multiprocessing.pool import ThreadPool
 from pathlib import Path
@@ -461,7 +462,7 @@ def main(opt):
                     r, _, t = run(**vars(opt), plots=False)
                     y.append(r + t)  # results and times
                 np.savetxt(f, y, fmt='%10.4g')  # save
-            os.system('zip -r study.zip study_*.txt')
+            subprocess.run('zip -r study.zip study_*.txt'.split())
             plot_val_study(x=x)  # plot
         else:
             raise NotImplementedError(f'--task {opt.task} not in ("train", "val", "test", "speed", "study")')

train.py

@@ -19,6 +19,7 @@ import argparse
 import math
 import os
 import random
+import subprocess
 import sys
 import time
 from copy import deepcopy
@@ -571,7 +572,8 @@ def main(opt, callbacks=Callbacks()):
         # ei = [isinstance(x, (int, float)) for x in hyp.values()]  # evolvable indices
         evolve_yaml, evolve_csv = save_dir / 'hyp_evolve.yaml', save_dir / 'evolve.csv'
         if opt.bucket:
-            os.system(f'gsutil cp gs://{opt.bucket}/evolve.csv {evolve_csv}')  # download evolve.csv if exists
+            subprocess.run(
+                f'gsutil cp gs://{opt.bucket}/evolve.csv {evolve_csv}'.split())  # download evolve.csv if exists
 
         for _ in range(opt.evolve):  # generations to evolve
             if evolve_csv.exists():  # if evolve.csv exists: select best hyps and mutate

utils/downloads.py

@@ -50,7 +50,8 @@ def safe_download(file, url, url2=None, min_bytes=1E0, error_msg=''):
         if file.exists():
             file.unlink()  # remove partial downloads
         LOGGER.info(f'ERROR: {e}\nRe-attempting {url2 or url} to {file}...')
-        os.system(f"curl -# -L '{url2 or url}' -o '{file}' --retry 3 -C -")  # curl download, retry and resume on fail
+        subprocess.run(
+            f"curl -# -L '{url2 or url}' -o '{file}' --retry 3 -C -".split())  # curl download, retry and resume on fail
     finally:
         if not file.exists() or file.stat().st_size < min_bytes:  # check
             if file.exists():

utils/general.py

@@ -631,8 +631,7 @@ def download(url, dir='.', unzip=True, delete=True, curl=False, threads=1, retry
             for i in range(retry + 1):
                 if curl:
                     s = 'sS' if threads > 1 else ''  # silent
-                    r = os.system(
-                        f'curl -# -{s}L "{url}" -o "{f}" --retry 9 -C -')  # curl download with retry, continue
+                    r = subprocess.run(f'curl -# -{s}L "{url}" -o "{f}" --retry 9 -C -'.split())
                     success = r == 0
                 else:
                     torch.hub.download_url_to_file(url, f, progress=threads == 1)  # torch download

val.py

@@ -22,6 +22,7 @@ Usage - formats:
 import argparse
 import json
 import os
+import subprocess
 import sys
 from pathlib import Path
 
@@ -397,7 +398,7 @@ def main(opt):
                     r, _, t = run(**vars(opt), plots=False)
                     y.append(r + t)  # results and times
                 np.savetxt(f, y, fmt='%10.4g')  # save
-            os.system('zip -r study.zip study_*.txt')
+            subprocess.run('zip -r study.zip study_*.txt'.split())
             plot_val_study(x=x)  # plot
         else:
             raise NotImplementedError(f'--task {opt.task} not in ("train", "val", "test", "speed", "study")')