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-rw-r--r--megapixels/commands/datasets/vecs_to_uuid.py56
1 files changed, 56 insertions, 0 deletions
diff --git a/megapixels/commands/datasets/vecs_to_uuid.py b/megapixels/commands/datasets/vecs_to_uuid.py
new file mode 100644
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+++ b/megapixels/commands/datasets/vecs_to_uuid.py
@@ -0,0 +1,56 @@
+"""
+Crop images to prepare for training
+"""
+
+import click
+
+from app.settings import types
+from app.utils import click_utils
+from app.settings import app_cfg as cfg
+
+@click.command()
+@click.option('-i', '--input', 'opt_fp_in', required=True,
+ help='Input directory')
+@click.option('-r', '--records', 'opt_fp_records', required=True,
+ help='Input directory')
+@click.option('-o', '--output', 'opt_fp_out', required=True,
+ help='Output JSON')
+@click.option('-f', '--force', 'opt_force', is_flag=True,
+ help='Force overwrite file')
+@click.pass_context
+def cli(ctx, opt_fp_in, opt_fp_records, opt_fp_out,opt_force):
+ """Merges UUID with face vectors"""
+
+ import sys
+ import os
+ from os.path import join
+ from pathlib import Path
+
+ from tqdm import tqdm
+ import pandas as pd
+
+ from app.utils import logger_utils, file_utils
+
+ # -------------------------------------------------
+ # init here
+
+ log = logger_utils.Logger.getLogger()
+
+ df_vecs = pd.read_csv(opt_fp_in)
+ df_records = pd.read_csv(opt_fp_records)
+ nrows = len(df_vecs)
+
+ # face vecs
+ uuid_vecs = {}
+
+ for roi_idx, row in tqdm(df_vecs.iterrows(), total=nrows):
+ # make image path
+ record_id = int(row['id'])
+ uuid = df_records.iloc[record_id]['uuid']
+ vec = row['vec'].split(',')
+ uuid_vecs[uuid] = vec
+
+ # save as JSON
+ file_utils.write_json(uuid_vecs, opt_fp_out)
+
+ \ No newline at end of file