fix roi index, clean up pose, roi, records, vector

1 files changed, 18 insertions, 26 deletions

diff --git a/megapixels/commands/cv/face_vector.py b/megapixels/commands/cv/face_vector.py
index 7200d73b..7c03205c 100644
--- a/megapixels/commands/cv/face_vector.py
+++ b/megapixels/commands/cv/face_vector.py
@@ -15,7 +15,7 @@ from app.settings import app_cfg as cfg
   help='Override enum media directory')
 @click.option('--data_store', 'opt_data_store',
   type=cfg.DataStoreVar,
-  default=click_utils.get_default(types.DataStore.SSD),
+  default=click_utils.get_default(types.DataStore.HDD),
   show_default=True,
   help=click_utils.show_help(types.Dataset))
 @click.option('--dataset', 'opt_dataset',
@@ -90,36 +90,28 @@ def cli(ctx, opt_fp_out, opt_dir_media, opt_data_store, opt_dataset, opt_size,
   log.debug('processing {:,} groups'.format(len(df_img_groups)))
 
   vecs = []
-
-  for image_index, df_img_group in tqdm(df_img_groups):
+  for record_index, df_img_group in tqdm(df_img_groups):
     # make fp
-    roi_index = df_img_group.index.values[0]
-    # log.debug(f'roi_index: {roi_index}, image_index: {image_index}')
-    ds_file = df_record.loc[roi_index]  # locate image meta
-    #ds_file = df_record.loc['index', image_index]  # locate image meta
-
-    fp_im = data_store.face(str(ds_file.subdir), str(ds_file.fn), str(ds_file.ext))
+    ds_record = df_record.iloc[record_index]
+    fp_im = data_store.face(ds_record.subdir, ds_record.fn, ds_record.ext)
     im = cv.imread(fp_im)
-    # get bbox
-    x = df_img_group.x.values[0]
-    y = df_img_group.y.values[0]
-    w = df_img_group.w.values[0]
-    h = df_img_group.h.values[0]
-    imw = df_img_group.image_width.values[0]
-    imh = df_img_group.image_height.values[0]
-    dim = im.shape[:2][::-1]
-    # get face vector
-    dim = (imw, imh)
-    bbox_dim = BBox.from_xywh(x, y, w, h).to_dim(dim)  # convert to int real dimensions
-    # compute vec
-    # padding=opt_padding not yet implemented in 19.16 but merged in master
-    vec = facerec.vec(im, bbox_dim, jitters=opt_jitters)
-    vec_str = ','.join([repr(x) for x in vec])  # convert to string for CSV
-    vecs.append( {'roi_index': roi_index, 'record_index': image_index, 'vec': vec_str})
+    for roi_index, df_img in df_img_group.iterrows():
+      # get bbox
+      x, y, w, h = df_img.x, df_img.y, df_img.w, df_img.h
+      dim = (ds_record.width, ds_record.height)
+      #dim = im.shape[:2][::-1]
+      # get face vector
+      bbox_dim = BBox.from_xywh(x, y, w, h).to_dim(dim)  # convert to int real dimensions
+      # compute vec
+      # padding=opt_padding not yet implemented in 19.16 but merged in master
+      vec = facerec.vec(im, bbox_dim, jitters=opt_jitters)
+      vec_str = ','.join([repr(x) for x in vec])  # convert to string for CSV
+      vecs.append( {'roi_index': roi_index, 'record_index': record_index, 'vec': vec_str})
 
 
-  # save date
+  # create dataframe
   df = pd.DataFrame.from_dict(vecs)
   df.index.name = 'index'
+  # save CSV
   file_utils.mkdirs(fp_out)
   df.to_csv(fp_out)
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