import pandas as pd
import os
import sys

target_dir = str(sys.argv[1])

full_list = os.listdir(target_dir)
csv_list = [file for file in full_list if file.startswith('cam')]
csv_list = sorted(csv_list)
#csv_list = [cam1.csv,cam2.csv]
#print(csv_list)

d1 = pd.read_csv(os.path.join(target_dir,csv_list[0]))
d2 = pd.read_csv(os.path.join(target_dir,csv_list[1]))

d2['x'] = 1920 - d2['x']

df_conc = pd.concat([d1,d2])

df_conc.sort_values(by='frame')
df_conc.drop_duplicates(['frame'])
#print(df_conc)

df_global = pd.DataFrame(index=range(0,int(df_conc['frame'].iloc[-1])+1), columns=['x','y','z','frame'])
df_global['frame'] = list(range(1, int(df_conc['frame'].iloc[-1]+2)))
df_global = df_global.astype({'frame':'int'})
#print(df_global)

df_global = pd.concat([df_global,df_conc])

df_global=df_global.sort_values(by = ['frame'])
df_global = df_global.drop_duplicates(['frame'], keep='last')
df_global = df_global.reset_index(drop=True)
df_global = df_global.interpolate()
df_global = df_global.interpolate(method='values')
#print(df_global)


df_global['x'] = 10 * ((df_global['x'] - df_global['x'].min()) / (df_global['x'].max() - df_global['x'].min())) - 5
df_global['y'] = 10 * ((df_global['y'] - df_global['y'].min()) / (df_global['y'].max() - df_global['y'].min())) - 5
df_global['z'] = 2.7 * ((df_global['z'] - df_global['z'].min()) / (df_global['z'].max() - df_global['z'].min())) + 0.3
#print(df_global)

df_global = df_global.fillna(0)
df_summary = df_global[df_global['frame']% 30 == 1]
#print(df_summary)
df_global.to_csv(os.path.join(target_dir,'coordinate.csv'))
df_summary.to_csv(os.path.join(target_dir,'coordinate_summary.csv'))