def get_next_obj_detect_img(project, currentId=None, dset=cfg.UNLABELED,
include_preds=True):
fold = data.load_fold(project)
ids = list(fold[dset].keys())
random.shuffle(ids)
img = data.load_obj_detect_img(ids[0], project, include_preds)
return make_obj_detect_image(ids[0], project, img)
def get_random_batch(proj_name, dset, shuffle=False, limit=20):
fold = data.load_fold(proj_name)
ids = list(fold[dset].keys())
if shuffle:
random.shuffle(ids)
image_data = []
for id_ in ids[:limit]:
image_data.append(make_image(id_, fold, dset))
return image_data
def add_image(src, tags, modelTags, id_=None, dset=None):
fold = data.load_fold(cfg.FOLD_FPATH)
image_data = get_image_data(fold, dset, shuffle=False, limit=20)
image = Image(id=id_,
project=fold.name,
src=src,
tags=tags,
modelTags=modelTags)
image_data[image.id] = image
return image
def save_obj_detect_image(id_, project, annos, dset=None):
dset = get_random_dset() if dset is None else dset
entry = data.make_obj_detect_entry(annos)
fold = data.load_fold(project)
if id_ in fold[cfg.UNLABELED]:
data.move_unlabeled_to_labeled(fold, dset, id_, entry)
else:
for dset in [cfg.VAL, cfg.TRAIN]:
if id_ in fold[dset]:
fold[dset][id_] = entry
break
def get_ranked_batch(proj_name, dset, limit=cfg.BATCH_SIZE):
fold = data.load_fold(proj_name)
preds_df = pd.read_csv(data.get_fpath(proj_name, cfg.RANKINGS_FNAME),
index_col=0)
i = 0
image_data = []
for id_, row in preds_df.iterrows():
if i > limit:
return image_data
if id_ in fold[dset]:
image_data.append(make_image(id_, fold, dset))
i += 1
return image_data
def update_tags(id_, project, tags):
print('updating tags', id_, project, tags)
if len(tags) > 0:
fold = data.load_fold(project)
print(fold.keys())
save_image_data(fold, id_, tags)
def get_image_single(id_, dset=cfg.UNLABELED):
print('get image single')
fold = data.load_fold(cfg.FOLD_FPATH)
return make_image(id_, fold, dset)
def get_image(project, id_, dset=cfg.UNLABELED):
fold = data.load_fold(project)
return make_image(id_, fold, dset)
def update_tags(id_, project, tags):
if len(tags) > 0:
fold = data.load_fold(project)
save_image_data(fold, id_, tags)
def get_image_single(project, id_, dset=cfg.UNLABELED):
fpath = data.get_fpath(project, cfg.FOLD_FNAME)
fold = data.load_fold(fpath)
return make_image(id_, fold, dset)