response[f"{counter}"][columns[0]["name"]] = tuple["data"][0]["intData"]
response[f"{counter}"][columns[1]["name"]] = tuple["data"][1]["stringData"]
response[f"{counter}"][columns[2]["name"]] = tuple["data"][2]["intData"]
response[f"{counter}"][columns[3]["name"]] = tuple["data"][3]["stringData"]
response[f"{counter}"][columns[4]["name"]] = tuple["data"][4]["floatData"]
counter += 1
df = pd.DataFrame.from_dict(response)
df_t = df.T
print(df_t)
df_t=df_t.drop_duplicates(['box_id'])
df_new = df_t.groupby(['keyframe_id', 'video_id','object','start_time']).size().reset_index(name="count")
result = df_new[df_new["count"] >= 1].sort_values(by=['count'],ascending=False)
print(result)
with tqdm(total=result.shape[0]) as pbar:
for row in tqdm(result.iterrows()):
pbar.update(1)
entry = {
'video_id': Literal(stringData = row[1]["video_id"]),
'keyframe_id': Literal(intData=int(row[1]["keyframe_id"])),
'object': Literal(stringData = row[1]["object"]),
'count': Literal(intData = row[1]["count"]),
'start_time':Literal(floatData = float(row[1]["start_time"])),
}
client.insert('tal_db', 'object_count', entry)
