model packaging/uploading

models/scripts/plot.py

@@ -0,0 +1,62 @@
+import os
+import sys
+import more_itertools
+import numpy as np
+import argparse
+
+parser = argparse.ArgumentParser(
+                    prog='plot',
+                    description='Print metrics',
+                    epilog='...')
+parser.add_argument('stem1', default='nohup.out.eynollah-206-noautosize-keepseps-refactoring9-crop-after2')
+parser.add_argument('stem2', default='eval-gt2-onlyfg-pixel-f1-v0.5-206-noautosize-keepseps-refactoring9-crop-after2')
+
+def main():
+    args = parser.parse_args()
+
+    prefix = os.path.dirname(sys.argv[0])
+    files = [path for path in os.listdir(prefix)
+             if path.startswith(args.stem1)
+             and path.endswith('.txt')]
+
+    for path in files:
+        name = path[len(args.stem1):]
+        metric = name.split('.')[-2]
+        series = name[:-(len(metric) + 5)]
+        path = os.path.join(prefix, path)
+
+        if metric == 'peak-vram':
+            cat, peak = np.loadtxt(path, unpack=True, dtype=np.dtype([("category", "U15"), ("peak", float)]))
+            peak //= 1024
+            peak //= 1024
+            print(metric, f"{series: <52}", dict(zip(cat.tolist(), peak.tolist())))
+        else:
+            val = np.loadtxt(path)
+            print(metric, f"{series: <52}", {'µ': float(np.round(np.mean(val), 2)),
+                                             'M': float(np.round(np.median(val), 2)),
+                                             'min': float(np.min(val)),
+                                             'max': float(np.max(val))})
+
+
+    files = [path for path in os.listdir(prefix)
+             if path.startswith(args.stem2)
+             and path.endswith('.log')]
+
+
+    for path in files:
+        name = path[len(args.stem2):]
+        series = name[:-4]
+        path = os.path.join(prefix, path)
+        with open(path, 'r') as fd:
+            lines = fd.readlines()
+        result_v0_5 = {}
+        result_v206 = {}
+        for metric, v0_5, v206 in more_itertools.chunked(lines, n=3, strict=True):
+            metric = metric[len(prefix) + 1:-1]
+            result_v0_5[metric] = float(np.round(float(v0_5.strip()), 3))
+            result_v206[metric] = float(np.round(float(v206.strip()), 3))
+        print("pixel-f1", f"{series: <52}", result_v206)
+
+    print("pixel-f1", "v0.5                                       ", result_v0_5)
+
+