├── .gitignore ├── Preview1.png ├── Preview2.png ├── README.md ├── build_csv.py ├── data.csv ├── detect_save_images.py ├── face_detect_recognition.py ├── face_detrec_video.py ├── face_recognition.py ├── haarcascade_frontalface_default.xml ├── input_images ├── IMG_1037.JPG ├── IMG_1038.JPG ├── IMG_1039.JPG ├── IMG_1040.JPG ├── IMG_1041.JPG ├── IMG_1042.JPG ├── IMG_1043.JPG ├── IMG_1044.JPG ├── IMG_1046.JPG ├── IMG_1047.JPG ├── IMG_1048.JPG ├── IMG_1049.JPG ├── IMG_1050.JPG ├── IMG_1051.JPG ├── IMG_1052.JPG ├── IMG_1053.JPG ├── IMG_1054.JPG ├── IMG_1055.JPG ├── IMG_1056.JPG ├── IMG_1057.JPG ├── IMG_1058.JPG ├── IMG_1059.JPG ├── IMG_1060.JPG ├── IMG_1061.JPG ├── IMG_1062.JPG ├── IMG_1063.JPG ├── IMG_1064.JPG ├── IMG_1065.JPG ├── IMG_1066.JPG ├── IMG_1067.JPG ├── IMG_1068.JPG ├── IMG_1069.JPG ├── IMG_1070.JPG ├── IMG_1071.JPG ├── IMG_1072.JPG ├── IMG_1073.JPG ├── IMG_1074.JPG ├── IMG_1075.JPG ├── IMG_1076.JPG ├── IMG_1077.JPG ├── IMG_1078.JPG ├── IMG_1079.JPG ├── IMG_1080.JPG ├── IMG_1081.JPG ├── IMG_1082.JPG ├── IMG_1083.JPG ├── IMG_1084.JPG ├── IMG_1085.JPG ├── IMG_1086.JPG ├── IMG_1087.JPG ├── IMG_1088.JPG ├── IMG_1089.JPG ├── IMG_1090.JPG ├── IMG_1091.JPG ├── IMG_1092.JPG ├── IMG_1093.JPG ├── IMG_1094.JPG ├── IMG_1095.JPG ├── IMG_1096.JPG ├── IMG_1097.JPG ├── IMG_1098.JPG ├── IMG_1099.JPG ├── IMG_1100.JPG ├── IMG_1101.JPG ├── IMG_1102.JPG ├── IMG_1103.JPG ├── IMG_1104.JPG ├── IMG_1105.JPG ├── IMG_1106.JPG ├── IMG_1107.JPG ├── IMG_1108.JPG ├── IMG_1109.JPG ├── IMG_1110.JPG ├── IMG_1111.JPG ├── IMG_1112.JPG ├── IMG_1113.JPG ├── IMG_1114.JPG ├── IMG_1115.JPG ├── IMG_1116.JPG ├── IMG_1117.JPG ├── IMG_1118.JPG ├── IMG_1119.JPG ├── IMG_1120.JPG ├── IMG_1121.JPG ├── IMG_1122.JPG ├── IMG_1123.JPG ├── IMG_1124.JPG ├── IMG_1125.JPG ├── IMG_1126.JPG ├── IMG_1127.JPG ├── IMG_1128.JPG ├── IMG_1129.JPG ├── IMG_1130.JPG ├── IMG_1131.JPG ├── IMG_1132.JPG ├── IMG_1133.JPG ├── IMG_1134.JPG ├── IMG_1135.JPG ├── IMG_1136.JPG ├── IMG_1137.JPG ├── IMG_1138.JPG ├── IMG_1139.JPG ├── IMG_1140.JPG ├── IMG_1141.JPG ├── IMG_1142.JPG ├── IMG_1144.JPG ├── IMG_1145.JPG ├── IMG_1146.JPG ├── IMG_1147.JPG ├── IMG_1148.JPG ├── IMG_1149.JPG ├── IMG_1150.JPG ├── IMG_1151.JPG ├── IMG_1152.JPG ├── IMG_1153.JPG ├── IMG_1154.JPG ├── IMG_1155.JPG ├── IMG_1156.JPG ├── IMG_1157.JPG ├── IMG_1158.JPG ├── IMG_1159.JPG ├── IMG_1160.JPG ├── IMG_1161.JPG ├── IMG_1162.JPG ├── IMG_1163.JPG ├── IMG_1164.JPG ├── IMG_1165.JPG ├── IMG_1166.JPG ├── IMG_1167.JPG ├── IMG_1168.JPG ├── IMG_1169.JPG ├── IMG_1170.JPG ├── IMG_1171.JPG ├── IMG_1172.JPG ├── IMG_1173.JPG ├── IMG_1174.JPG ├── IMG_1175.JPG ├── IMG_1176.JPG ├── IMG_1177.JPG ├── IMG_1178.JPG ├── IMG_1179.JPG ├── IMG_1180.JPG ├── IMG_1181.JPG ├── IMG_1182.JPG ├── IMG_1183.JPG ├── IMG_1184.JPG ├── IMG_1185.JPG ├── IMG_1186.JPG ├── IMG_1187.JPG ├── IMG_1188.JPG ├── IMG_1189.JPG ├── IMG_1190.JPG ├── IMG_1191.JPG ├── IMG_1192.JPG ├── IMG_1193.JPG ├── IMG_1194.JPG ├── IMG_1195.JPG ├── IMG_1196.JPG ├── IMG_1197.JPG ├── IMG_1198.JPG ├── IMG_1199.JPG ├── IMG_1200.JPG ├── IMG_1201.JPG ├── IMG_1202.JPG ├── IMG_1203.JPG ├── IMG_1204.JPG ├── IMG_1205.JPG ├── IMG_1206.JPG ├── IMG_1207.JPG ├── IMG_1208.JPG ├── IMG_1209.JPG ├── IMG_1210.JPG ├── IMG_1211.JPG ├── IMG_1212.JPG ├── IMG_1213.JPG ├── IMG_1214.JPG ├── IMG_1215.JPG ├── IMG_1216.JPG ├── IMG_1217.JPG ├── IMG_1218.JPG ├── IMG_1219.JPG ├── IMG_1220.JPG ├── IMG_1221.JPG ├── IMG_1222.JPG ├── IMG_1223.JPG ├── IMG_1224.JPG ├── IMG_1225.JPG ├── IMG_1226.JPG ├── IMG_1227.JPG ├── IMG_1228.JPG ├── IMG_1229.JPG ├── IMG_1230.JPG ├── IMG_1231.JPG ├── IMG_1232.JPG ├── IMG_1233.JPG ├── IMG_1234.JPG ├── IMG_1235.JPG ├── IMG_1236.JPG ├── IMG_1237.JPG ├── IMG_1238.JPG ├── IMG_1239.JPG ├── IMG_1240.JPG ├── IMG_1241.JPG ├── IMG_1242.JPG ├── IMG_1243.JPG ├── IMG_1244.JPG ├── IMG_1245.JPG ├── IMG_1246.JPG ├── IMG_1247.JPG ├── IMG_1248.JPG ├── IMG_1249.JPG ├── IMG_1250.JPG ├── IMG_1251.JPG ├── IMG_1252.JPG ├── IMG_1253.JPG ├── IMG_1254.JPG ├── IMG_1255.JPG ├── IMG_1256.JPG ├── IMG_1257.JPG ├── IMG_1258.JPG ├── IMG_1259.JPG ├── IMG_1260.JPG ├── IMG_1261.JPG ├── IMG_1262.JPG ├── IMG_1263.JPG ├── IMG_1264.JPG ├── IMG_1265.JPG ├── IMG_1266.JPG ├── IMG_1267.JPG ├── IMG_1268.JPG ├── IMG_1269.JPG ├── IMG_1270.JPG ├── IMG_1271.JPG ├── IMG_1272.JPG ├── IMG_1273.JPG ├── IMG_1274.JPG ├── IMG_1275.JPG ├── IMG_1276.JPG ├── IMG_1277.JPG ├── IMG_1278.JPG ├── IMG_1279.JPG ├── IMG_1280.JPG ├── IMG_1281.JPG ├── IMG_1282.JPG ├── IMG_1283.JPG ├── IMG_1284.JPG ├── IMG_1285.JPG ├── IMG_1286.JPG ├── IMG_1287.JPG ├── IMG_1288.JPG ├── IMG_1289.JPG ├── IMG_1290.JPG ├── IMG_1291.JPG ├── IMG_1292.JPG ├── IMG_1293.JPG ├── IMG_1294.JPG ├── IMG_1295.JPG ├── IMG_1296.JPG ├── IMG_1297.JPG ├── IMG_1298.JPG ├── IMG_1299.JPG ├── IMG_1300.JPG ├── IMG_1301.JPG └── IMG_1302.JPG ├── output_images ├── IMG_1037.JPG.jpg ├── IMG_1039.JPG.jpg ├── IMG_1041.JPG.jpg ├── IMG_1042.JPG.jpg ├── IMG_1043.JPG.jpg ├── IMG_1044.JPG.jpg ├── IMG_1046.JPG.jpg ├── IMG_1047.JPG.jpg ├── IMG_1049.JPG.jpg ├── IMG_1050.JPG.jpg ├── IMG_1051.JPG.jpg ├── IMG_1052.JPG.jpg ├── IMG_1053.JPG.jpg ├── IMG_1054.JPG.jpg ├── IMG_1056.JPG.jpg ├── IMG_1059.JPG.jpg ├── IMG_1060.JPG.jpg ├── IMG_1063.JPG.jpg ├── IMG_1064.JPG.jpg ├── IMG_1065.JPG.jpg ├── IMG_1068.JPG.jpg ├── IMG_1069.JPG.jpg ├── IMG_1070.JPG.jpg ├── IMG_1071.JPG.jpg ├── IMG_1072.JPG.jpg ├── IMG_1073.JPG.jpg ├── IMG_1074.JPG.jpg ├── IMG_1075.JPG.jpg ├── IMG_1076.JPG.jpg ├── IMG_1077.JPG.jpg ├── IMG_1078.JPG.jpg ├── IMG_1079.JPG.jpg ├── IMG_1080.JPG.jpg ├── IMG_1086.JPG.jpg ├── IMG_1087.JPG.jpg ├── IMG_1088.JPG.jpg ├── IMG_1089.JPG.jpg ├── IMG_1090.JPG.jpg ├── IMG_1091.JPG.jpg ├── IMG_1092.JPG.jpg ├── IMG_1093.JPG.jpg ├── IMG_1094.JPG.jpg ├── IMG_1095.JPG.jpg ├── IMG_1096.JPG.jpg ├── IMG_1097.JPG.jpg ├── IMG_1098.JPG.jpg ├── IMG_1099.JPG.jpg ├── IMG_1100.JPG.jpg ├── IMG_1101.JPG.jpg ├── IMG_1102.JPG.jpg ├── IMG_1103.JPG.jpg ├── IMG_1104.JPG.jpg ├── IMG_1105.JPG.jpg ├── IMG_1106.JPG.jpg ├── IMG_1107.JPG.jpg ├── IMG_1108.JPG.jpg ├── IMG_1109.JPG.jpg ├── IMG_1110.JPG.jpg ├── IMG_1111.JPG.jpg ├── IMG_1112.JPG.jpg ├── IMG_1113.JPG.jpg ├── IMG_1114.JPG.jpg ├── IMG_1115.JPG.jpg ├── IMG_1116.JPG.jpg ├── IMG_1117.JPG.jpg ├── IMG_1118.JPG.jpg ├── IMG_1119.JPG.jpg ├── IMG_1121.JPG.jpg ├── IMG_1122.JPG.jpg ├── IMG_1123.JPG.jpg ├── IMG_1124.JPG.jpg ├── IMG_1125.JPG.jpg ├── IMG_1126.JPG.jpg ├── IMG_1127.JPG.jpg ├── IMG_1128.JPG.jpg ├── IMG_1129.JPG.jpg ├── IMG_1130.JPG.jpg ├── IMG_1131.JPG.jpg ├── IMG_1132.JPG.jpg ├── IMG_1133.JPG.jpg ├── IMG_1134.JPG.jpg ├── IMG_1135.JPG.jpg ├── IMG_1136.JPG.jpg ├── IMG_1137.JPG.jpg ├── IMG_1138.JPG.jpg ├── IMG_1139.JPG.jpg ├── IMG_1140.JPG.jpg ├── IMG_1141.JPG.jpg ├── IMG_1142.JPG.jpg ├── IMG_1144.JPG.jpg ├── IMG_1145.JPG.jpg ├── IMG_1146.JPG.jpg ├── IMG_1147.JPG.jpg ├── IMG_1148.JPG.jpg ├── IMG_1149.JPG.jpg ├── IMG_1150.JPG.jpg ├── IMG_1151.JPG.jpg ├── IMG_1152.JPG.jpg ├── IMG_1154.JPG.jpg ├── IMG_1155.JPG.jpg ├── IMG_1156.JPG.jpg ├── IMG_1157.JPG.jpg ├── IMG_1158.JPG.jpg ├── IMG_1159.JPG.jpg ├── IMG_1161.JPG.jpg ├── IMG_1162.JPG.jpg ├── IMG_1163.JPG.jpg ├── IMG_1164.JPG.jpg ├── IMG_1165.JPG.jpg ├── IMG_1166.JPG.jpg ├── IMG_1167.JPG.jpg ├── IMG_1169.JPG.jpg ├── IMG_1170.JPG.jpg ├── IMG_1171.JPG.jpg ├── IMG_1172.JPG.jpg ├── IMG_1173.JPG.jpg ├── IMG_1174.JPG.jpg ├── IMG_1175.JPG.jpg ├── IMG_1176.JPG.jpg ├── IMG_1177.JPG.jpg ├── IMG_1178.JPG.jpg ├── IMG_1179.JPG.jpg ├── IMG_1180.JPG.jpg ├── IMG_1181.JPG.jpg ├── IMG_1182.JPG.jpg ├── IMG_1184.JPG.jpg ├── IMG_1185.JPG.jpg ├── IMG_1186.JPG.jpg ├── IMG_1187.JPG.jpg ├── IMG_1188.JPG.jpg ├── IMG_1189.JPG.jpg ├── IMG_1190.JPG.jpg ├── IMG_1191.JPG.jpg ├── IMG_1192.JPG.jpg ├── IMG_1193.JPG.jpg ├── IMG_1194.JPG.jpg ├── IMG_1195.JPG.jpg ├── IMG_1196.JPG.jpg ├── IMG_1197.JPG.jpg ├── IMG_1198.JPG.jpg ├── IMG_1199.JPG.jpg ├── IMG_1200.JPG.jpg ├── IMG_1201.JPG.jpg ├── IMG_1202.JPG.jpg ├── IMG_1203.JPG.jpg ├── IMG_1204.JPG.jpg ├── IMG_1205.JPG.jpg ├── IMG_1206.JPG.jpg ├── IMG_1207.JPG.jpg ├── IMG_1208.JPG.jpg ├── IMG_1209.JPG.jpg ├── IMG_1210.JPG.jpg ├── IMG_1211.JPG.jpg ├── IMG_1212.JPG.jpg ├── IMG_1213.JPG.jpg ├── IMG_1214.JPG.jpg ├── IMG_1215.JPG.jpg ├── IMG_1216.JPG.jpg ├── IMG_1217.JPG.jpg ├── IMG_1218.JPG.jpg ├── IMG_1219.JPG.jpg ├── IMG_1220.JPG.jpg ├── IMG_1221.JPG.jpg ├── IMG_1222.JPG.jpg ├── IMG_1223.JPG.jpg ├── IMG_1224.JPG.jpg ├── IMG_1225.JPG.jpg ├── IMG_1226.JPG.jpg ├── IMG_1227.JPG.jpg ├── IMG_1228.JPG.jpg ├── IMG_1229.JPG.jpg ├── IMG_1230.JPG.jpg ├── IMG_1231.JPG.jpg ├── IMG_1232.JPG.jpg ├── IMG_1233.JPG.jpg ├── IMG_1234.JPG.jpg ├── IMG_1235.JPG.jpg ├── IMG_1236.JPG.jpg ├── IMG_1237.JPG.jpg ├── IMG_1238.JPG.jpg ├── IMG_1239.JPG.jpg ├── IMG_1240.JPG.jpg ├── IMG_1241.JPG.jpg ├── IMG_1242.JPG.jpg ├── IMG_1243.JPG.jpg ├── IMG_1244.JPG.jpg ├── IMG_1245.JPG.jpg ├── IMG_1246.JPG.jpg ├── IMG_1247.JPG.jpg ├── IMG_1248.JPG.jpg ├── IMG_1249.JPG.jpg ├── IMG_1250.JPG.jpg ├── IMG_1251.JPG.jpg ├── IMG_1252.JPG.jpg ├── IMG_1253.JPG.jpg ├── IMG_1254.JPG.jpg ├── IMG_1255.JPG.jpg ├── IMG_1256.JPG.jpg ├── IMG_1257.JPG.jpg ├── IMG_1258.JPG.jpg ├── IMG_1259.JPG.jpg ├── IMG_1260.JPG.jpg ├── IMG_1261.JPG.jpg ├── IMG_1262.JPG.jpg ├── IMG_1263.JPG.jpg ├── IMG_1264.JPG.jpg ├── IMG_1265.JPG.jpg ├── IMG_1266.JPG.jpg ├── IMG_1267.JPG.jpg ├── IMG_1268.JPG.jpg ├── IMG_1274.JPG.jpg ├── IMG_1275.JPG.jpg ├── IMG_1276.JPG.jpg ├── IMG_1277.JPG.jpg ├── IMG_1278.JPG.jpg ├── IMG_1279.JPG.jpg ├── IMG_1280.JPG.jpg ├── IMG_1281.JPG.jpg ├── IMG_1282.JPG.jpg ├── IMG_1283.JPG.jpg ├── IMG_1284.JPG.jpg ├── IMG_1285.JPG.jpg ├── IMG_1286.JPG.jpg ├── IMG_1287.JPG.jpg ├── IMG_1288.JPG.jpg ├── IMG_1289.JPG.jpg ├── IMG_1290.JPG.jpg ├── IMG_1291.JPG.jpg ├── IMG_1292.JPG.jpg ├── IMG_1293.JPG.jpg ├── IMG_1294.JPG.jpg ├── IMG_1295.JPG.jpg ├── IMG_1296.JPG.jpg ├── IMG_1297.JPG.jpg ├── IMG_1298.JPG.jpg ├── IMG_1299.JPG.jpg ├── IMG_1300.JPG.jpg ├── IMG_1301.JPG.jpg └── IMG_1302.JPG.jpg ├── resize_rotate_images.py └── sorted_output_images ├── .DS_Store ├── pankaj ├── IMG_1185.JPG.jpg ├── IMG_1188.JPG.jpg ├── IMG_1189.JPG.jpg ├── IMG_1190.JPG.jpg ├── IMG_1191.JPG.jpg ├── IMG_1193.JPG.jpg ├── IMG_1194.JPG.jpg ├── IMG_1196.JPG.jpg ├── IMG_1197.JPG.jpg ├── IMG_1198.JPG.jpg ├── IMG_1199.JPG.jpg ├── IMG_1203.JPG.jpg ├── IMG_1204.JPG.jpg ├── IMG_1208.JPG.jpg ├── IMG_1209.JPG.jpg ├── IMG_1210.JPG.jpg ├── IMG_1212.JPG.jpg ├── IMG_1214.JPG.jpg ├── IMG_1215.JPG.jpg ├── IMG_1217.JPG.jpg ├── IMG_1218.JPG.jpg ├── IMG_1219.JPG.jpg ├── IMG_1220.JPG.jpg ├── IMG_1222.JPG.jpg ├── IMG_1223.JPG.jpg └── IMG_1227.JPG.jpg ├── pavan ├── IMG_1266.JPG.jpg ├── IMG_1267.JPG.jpg ├── IMG_1268.JPG.jpg ├── IMG_1274.JPG.jpg ├── IMG_1275.JPG.jpg ├── IMG_1276.JPG.jpg ├── IMG_1277.JPG.jpg ├── IMG_1279.JPG.jpg ├── IMG_1280.JPG.jpg ├── IMG_1281.JPG.jpg ├── IMG_1282.JPG.jpg ├── IMG_1283.JPG.jpg ├── IMG_1284.JPG.jpg ├── IMG_1285.JPG.jpg ├── IMG_1286.JPG.jpg ├── IMG_1287.JPG.jpg ├── IMG_1288.JPG.jpg ├── IMG_1289.JPG.jpg ├── IMG_1290.JPG.jpg ├── IMG_1292.JPG.jpg ├── IMG_1294.JPG.jpg ├── IMG_1298.JPG.jpg ├── IMG_1299.JPG.jpg ├── IMG_1300.JPG.jpg └── IMG_1301.JPG.jpg ├── praneeth ├── IMG_1089.JPG.jpg ├── IMG_1090.JPG.jpg ├── IMG_1091.JPG.jpg ├── IMG_1092.JPG.jpg ├── IMG_1094.JPG.jpg ├── IMG_1097.JPG.jpg ├── IMG_1099.JPG.jpg ├── IMG_1100.JPG.jpg ├── IMG_1101.JPG.jpg ├── IMG_1102.JPG.jpg ├── IMG_1104.JPG.jpg ├── IMG_1105.JPG.jpg ├── IMG_1106.JPG.jpg ├── IMG_1107.JPG.jpg ├── IMG_1108.JPG.jpg ├── IMG_1109.JPG.jpg ├── IMG_1112.JPG.jpg ├── IMG_1114.JPG.jpg └── IMG_1115.JPG.jpg ├── satish ├── IMG_1119.JPG.jpg ├── IMG_1121.JPG.jpg ├── IMG_1122.JPG.jpg ├── IMG_1123.JPG.jpg ├── IMG_1124.JPG.jpg ├── IMG_1125.JPG.jpg ├── IMG_1126.JPG.jpg ├── IMG_1127.JPG.jpg ├── IMG_1128.JPG.jpg ├── IMG_1129.JPG.jpg ├── IMG_1130.JPG.jpg ├── IMG_1131.JPG.jpg ├── IMG_1132.JPG.jpg ├── IMG_1133.JPG.jpg ├── IMG_1134.JPG.jpg ├── IMG_1135.JPG.jpg ├── IMG_1137.JPG.jpg ├── IMG_1141.JPG.jpg ├── IMG_1142.JPG.jpg ├── IMG_1144.JPG.jpg ├── IMG_1145.JPG.jpg ├── IMG_1146.JPG.jpg ├── IMG_1147.JPG.jpg └── IMG_1149.JPG.jpg ├── suraj ├── IMG_1064.JPG.jpg ├── IMG_1065.JPG.jpg ├── IMG_1068.JPG.jpg ├── IMG_1069.JPG.jpg ├── IMG_1071.JPG.jpg ├── IMG_1072.JPG.jpg ├── IMG_1073.JPG.jpg ├── IMG_1074.JPG.jpg ├── IMG_1075.JPG.jpg ├── IMG_1076.JPG.jpg ├── IMG_1077.JPG.jpg ├── IMG_1078.JPG.jpg ├── IMG_1079.JPG.jpg ├── IMG_1080.JPG.jpg ├── IMG_1083.JPG.jpg ├── IMG_1085.JPG.jpg ├── IMG_1086.JPG.jpg ├── IMG_1087.JPG.jpg └── IMG_1088.JPG.jpg └── surya ├── IMG_1228.JPG.jpg ├── IMG_1229.JPG.jpg ├── IMG_1230.JPG.jpg ├── IMG_1231.JPG.jpg ├── IMG_1232.JPG.jpg ├── IMG_1233.JPG.jpg ├── IMG_1234.JPG.jpg ├── IMG_1235.JPG.jpg ├── IMG_1236.JPG.jpg ├── IMG_1237.JPG.jpg ├── IMG_1238.JPG.jpg ├── IMG_1239.JPG.jpg ├── IMG_1240.JPG.jpg ├── IMG_1241.JPG.jpg ├── IMG_1243.JPG.jpg ├── IMG_1245.JPG.jpg ├── IMG_1246.JPG.jpg ├── IMG_1247.JPG.jpg ├── IMG_1248.JPG.jpg ├── IMG_1249.JPG.jpg ├── IMG_1251.JPG.jpg ├── IMG_1252.JPG.jpg ├── IMG_1255.JPG.jpg ├── IMG_1257.JPG.jpg ├── IMG_1258.JPG.jpg └── IMG_1260.JPG.jpg /.gitignore: -------------------------------------------------------------------------------- 1 | #ignore image files 2 | 3 | *.jpg 4 | *.png 5 | 6 | !Preview1.png 7 | !Preview2.png 8 | !input_images/* 9 | !output_images/* 10 | !sorted_output_images/*/* 11 | -------------------------------------------------------------------------------- /Preview1.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SnShine/FaceRecognizer/0db07cb6ea45f52d8aa2daf42b885a0626aee8f3/Preview1.png -------------------------------------------------------------------------------- /Preview2.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SnShine/FaceRecognizer/0db07cb6ea45f52d8aa2daf42b885a0626aee8f3/Preview2.png -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | ## FaceRecognizer 2 | 3 | A face recognition algorithm written in Python. 4 | 5 | Real-Time detection & prediction of subjects/persons in video recording with built-in camera. 6 | 7 | If there is any intruder (known/ unknown subjects) attack, it automatically posts on your Facebook timeline to notify you and your friends/neighbors. 8 | 9 | ## Preview 10 | Screen-shot while detecting & predicting subject(s) in real-time video. 11 | 12 | ![alt tag](../master/Preview1.png) 13 | 14 | Screen-shot of Facebook post regarding intruder attack. 15 | 16 | ![alt tag](../master/Preview2.png) 17 | 18 | ## Usage of available files 19 | 20 | |File Name|Used to| 21 | |---------|-------| 22 | |build_csv.py|build a csv file with paths to train images with labels.| 23 | |detect_save_images.py|detect faces and save cropped images to output folder.| 24 | |face_detect_recognition.py|detect & recognize faces in images and display them.| 25 | |**face_detrec_video.py**|detect & recognize intruders in real-time video and notifies on facebook| 26 | |face_recognition.py|train eigen_model & recognise faces in pre-cropped images| 27 | |resize_rotate_images.py|pre-process images and saves output to output_folder| 28 | -------------------------------------------------------------------------------- /build_csv.py: -------------------------------------------------------------------------------- 1 | ''' 2 | Surya Teja Cheedella 3 | shine123surya[at]gmail[dot]com 4 | BITS Pilani, Hyderabad Campus 5 | 6 | Takes all the images in folder which contains sub-folders of subjects/persons. 7 | Writes path to image files and labes (starting from 0) to a csv file. 8 | ''' 9 | 10 | from os import listdir 11 | 12 | if __name__== "__main__": 13 | # output csv file where we save paths to out images 14 | write_file= open("data.csv", "w") 15 | data_dir= "/home/suryateja/Documents/GitHub/FaceRecognizer/output_images" 16 | 17 | # folders for each subject in root images folder 18 | subjects= listdir(data_dir) 19 | #print(subjects) 20 | 21 | for i in range(len(subjects)): 22 | # all pictures in a particular folder/subject 23 | photos= listdir(data_dir+ "/"+ subjects[i]) 24 | for photo in photos: 25 | out_line= data_dir+ "/"+ subjects[i]+ "/"+ photo+ ";"+ str(i) 26 | # write the path and class of each picture to the csv file 27 | write_file.write(out_line) 28 | write_file.write("\n") 29 | print(out_line) 30 | -------------------------------------------------------------------------------- /data.csv: -------------------------------------------------------------------------------- 1 | /home/suryateja/Documents/GitHub/FaceRecognizer/output_images/surya/77.jpg;0 2 | /home/suryateja/Documents/GitHub/FaceRecognizer/output_images/surya/183.jpg;0 3 | /home/suryateja/Documents/GitHub/FaceRecognizer/output_images/surya/73.jpg;0 4 | /home/suryateja/Documents/GitHub/FaceRecognizer/output_images/surya/87.jpg;0 5 | /home/suryateja/Documents/GitHub/FaceRecognizer/output_images/surya/124.jpg;0 6 | 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/home/suryateja/Documents/GitHub/FaceRecognizer/output_images/pankaj/258.jpg;7 125 | /home/suryateja/Documents/GitHub/FaceRecognizer/output_images/pankaj/343.jpg;7 126 | /home/suryateja/Documents/GitHub/FaceRecognizer/output_images/pankaj/251.jpg;7 127 | /home/suryateja/Documents/GitHub/FaceRecognizer/output_images/pankaj/328.jpg;7 128 | /home/suryateja/Documents/GitHub/FaceRecognizer/output_images/pankaj/107.jpg;7 129 | /home/suryateja/Documents/GitHub/FaceRecognizer/output_images/pankaj/38.jpg;7 130 | /home/suryateja/Documents/GitHub/FaceRecognizer/output_images/pankaj/189.jpg;7 131 | /home/suryateja/Documents/GitHub/FaceRecognizer/output_images/pankaj/234.jpg;7 132 | /home/suryateja/Documents/GitHub/FaceRecognizer/output_images/pankaj/80.jpg;7 133 | -------------------------------------------------------------------------------- /detect_save_images.py: -------------------------------------------------------------------------------- 1 | ''' 2 | Surya Teja Cheedella 3 | shine123surya[at]gmail[dot]com 4 | BITS Pilani, Hyderabad Campus 5 | 6 | Takes all the images in "input_path" and analyses them for any faces. 7 | If face(s) is(are) found, it crops and saves them at "output_path". 8 | ''' 9 | 10 | import cv2 11 | import cv2.cv as cv 12 | from os import listdir 13 | import time 14 | 15 | def cropImage(img, box): 16 | [p, q, r, s]= box 17 | # crop and save the image provided with the co-ordinates of bounding box 18 | write_img_color= img[q:q+ s, p:p+ r] 19 | saveCropped(write_img_color, name) 20 | 21 | # save the cropped image at specified location 22 | def saveCropped(img, name): 23 | cv2.imwrite(output_path+ name+ ".jpg", img) 24 | 25 | if __name__== "__main__": 26 | # paths to input and output images 27 | input_path= "old/input_images/" 28 | output_path= "old/output_images/" 29 | 30 | # load pre-trained frontalface cascade classifier 31 | frontal_face= cv2.CascadeClassifier("haarcascade_frontalface_default.xml") 32 | input_names= listdir("/home/suryateja/Documents/GitHub/FaceRecognizer/"+ input_path) 33 | 34 | print("Starting to detect faces in images and save the cropped images to output file...") 35 | sttime= time.clock() 36 | i= 1 37 | for name in input_names: 38 | print(input_path+name) 39 | color_img= cv2.imread(input_path+ name) 40 | # converting color image to grayscale image 41 | gray_img= cv2.cvtColor(color_img, cv2.COLOR_BGR2GRAY) 42 | 43 | # find the bounding boxes around detected faces in images 44 | bBoxes= frontal_face.detectMultiScale(gray_img, scaleFactor=1.3, minNeighbors=5, minSize=(30, 30), flags = cv.CV_HAAR_SCALE_IMAGE) 45 | #print(bBoxes) 46 | 47 | for box in bBoxes: 48 | #print(box) 49 | # crop and save the image at specified location 50 | cropImage(color_img, box) 51 | i+= 1 52 | 53 | print("Successfully completed the task in %.2f Secs." % (time.clock()- sttime)) 54 | -------------------------------------------------------------------------------- /face_detect_recognition.py: -------------------------------------------------------------------------------- 1 | ''' 2 | Surya Teja Cheedella 3 | shine123surya[at]gmail[dot]com 4 | BITS Pilani, Hyderabad Campus 5 | 6 | Working: 7 | Takes images stored in first path and traines faceRecognizer models. 8 | For every image in second path, it first detects faces in images and 9 | then predicts subject/person with the help of trained model. 10 | 11 | Usage: 12 | face_detect_recognition.py 13 | 14 | Takes two arguments: 15 | 1. Input folder which contains sub-folders of subjects/ persons. 16 | There should be images saved in subfolders which are used to train. 17 | 2. Path to a folder consists of images for which we are gonna predict subject. 18 | Note: Images in here can be full sized images. (no need to crop faces) 19 | ''' 20 | 21 | import cv2 22 | import cv2.cv as cv 23 | import numpy as np 24 | from os import listdir 25 | import sys, time 26 | 27 | def get_images(path, size): 28 | ''' 29 | path: path to a folder which contains subfolders of for each subject/person 30 | which in turn cotains pictures of subjects/persons. 31 | 32 | size: a tuple to resize images. 33 | Ex- (256, 256) 34 | ''' 35 | sub= 0 36 | images, labels= [], [] 37 | people= [] 38 | 39 | for subdir in listdir(path): 40 | for image in listdir(path+ "/"+ subdir): 41 | #print(subdir, images) 42 | img= cv2.imread(path+"/"+subdir+"/"+image, cv2.IMREAD_GRAYSCALE) 43 | img= cv2.resize(img, size) 44 | 45 | images.append(np.asarray(img, dtype= np.uint8)) 46 | labels.append(sub) 47 | 48 | #cv2.imshow("win", img) 49 | #cv2.waitKey(10) 50 | 51 | people.append(subdir) 52 | sub+= 1 53 | 54 | return [images, labels, people] 55 | 56 | if __name__== "__main__": 57 | if len(sys.argv)!= 3: 58 | print("Wrong number of arguments! See the usage.\n") 59 | print("Usage: face_recognition.py ") 60 | sys.exit() 61 | 62 | [images, labels, people]= get_images(sys.argv[1], (256, 256)) 63 | #print([images, labels]) 64 | 65 | labels= np.asarray(labels, dtype= np.int32) 66 | 67 | # initializing eigen_model and training 68 | print("Initializing eigen FaceRecognizer and training...") 69 | sttime= time.clock() 70 | eigen_model= cv2.createEigenFaceRecognizer() 71 | eigen_model.train(images, labels) 72 | print("\tSuccessfully completed training in "+ str(time.clock()- sttime)+ " Secs!") 73 | 74 | # starting to detect & predict subject/ person in images. 75 | for image_name in listdir(sys.argv[2]): 76 | try: 77 | color_image= cv2.imread(sys.argv[2]+ "/"+ image_name) 78 | [x, y]= color_image.shape[:2] 79 | x_factor= (float(y)/x) 80 | resize_y= 480 81 | 82 | color_image= cv2.resize(color_image, (int(resize_y* x_factor), resize_y)) 83 | #it's better to convert color image to gray scale image rather than reading it from memory again! 84 | pre_image= cv2.imread(sys.argv[2]+ "/"+ image_name, cv2.IMREAD_GRAYSCALE) 85 | pre_image= cv2.resize(pre_image, (int(resize_y* x_factor), resize_y)) 86 | except: 87 | print("Couldn't read image. Please check the path to image file.") 88 | sys.exit() 89 | 90 | #starting to detect face in given image 91 | frontal_face= cv2.CascadeClassifier("haarcascade_frontalface_default.xml") 92 | #bBoxes= frontal_face.detectMultiScale(pre_image, scaleFactor=1.3, minNeighbors=5, minSize=(30, 30), flags = cv.CV_HAAR_SCALE_IMAGE) 93 | bBoxes= frontal_face.detectMultiScale(pre_image, scaleFactor=1.3, minNeighbors=4, minSize=(30, 30), flags = cv.CV_HAAR_SCALE_IMAGE) 94 | 95 | for bBox in bBoxes: 96 | (p,q,r,s)= bBox 97 | cv2.rectangle(color_image, (p,q), (p+r,q+s), (225,0,25), 2) 98 | #cv2.rectangle(pre_image, (p,q), (p+r,q+s), (25,0,225), 2) 99 | 100 | #starting to predict subject/ person in cropped (detected) image 101 | pre_crop_image= pre_image[q:q+s, p:p+r] 102 | pre_crop_image= cv2.resize(pre_crop_image, (256, 256)) 103 | 104 | [predicted_label, predicted_conf]= eigen_model.predict(np.asarray(pre_crop_image)) 105 | print("Predicted person in the image "+ image_name+ " : "+ people[predicted_label]) 106 | 107 | box_text= format("Subject: "+ people[predicted_label]) 108 | #print(box_text) 109 | 110 | cv2.putText(color_image, box_text, (p-20, q-5), cv2.FONT_HERSHEY_PLAIN, 1.1, (25,0,225), 1) 111 | 112 | cv2.imshow("Win1", color_image) 113 | #cv2.imshow("Win2", pre_crop_image) 114 | cv2.waitKey(0) 115 | 116 | #starting to predict subject/ person in cropped (detected) image 117 | -------------------------------------------------------------------------------- /face_detrec_video.py: -------------------------------------------------------------------------------- 1 | ''' 2 | Surya Teja Cheedella 3 | shine123surya[at]gmail[dot]com 4 | BITS Pilani, Hyderabad Campus 5 | 6 | Real-Time detection & prediction of subjects/persons in 7 | video recording by in-built camera. 8 | If there is any intruder (trained/ unknown subjects) attack, it posts on your 9 | facebook timeline to notify you and your friends/ neighbours. 10 | 11 | Working: 12 | Takes images stored in first path and traines faceRecognizer models. 13 | Then starts recording video from camera and shows detected subjects. 14 | 15 | Usage: 16 | face_detrec_video.py 17 | 18 | Takes one argument: 19 | 1. Input folder which contains sub-folders of subjects/ persons. 20 | There should be images saved in subfolders which are used to train. 21 | ''' 22 | 23 | import cv2 24 | import cv2.cv as cv 25 | import numpy as np 26 | import os 27 | import sys, time 28 | import requests, facebook 29 | 30 | def get_images(path, size): 31 | ''' 32 | path: path to a folder which contains subfolders of for each subject/person 33 | which in turn cotains pictures of subjects/persons. 34 | 35 | size: a tuple to resize images. 36 | Ex- (256, 256) 37 | ''' 38 | sub= 0 39 | images, labels= [], [] 40 | people= [] 41 | 42 | for subdir in os.listdir(path): 43 | for image in os.listdir(path+ "/"+ subdir): 44 | #print(subdir, images) 45 | img= cv2.imread(path+os.path.sep+subdir+os.path.sep+image, cv2.IMREAD_GRAYSCALE) 46 | img= cv2.resize(img, size) 47 | 48 | images.append(np.asarray(img, dtype= np.uint8)) 49 | labels.append(sub) 50 | 51 | #cv2.imshow("win", img) 52 | #cv2.waitKey(10) 53 | 54 | people.append(subdir) 55 | sub+= 1 56 | 57 | return [images, labels, people] 58 | 59 | def detect_faces(image): 60 | ''' 61 | Takes an image as input and returns an array of bounding box(es). 62 | ''' 63 | frontal_face= cv2.CascadeClassifier("haarcascade_frontalface_default.xml") 64 | bBoxes= frontal_face.detectMultiScale(image, scaleFactor=1.3, minNeighbors=4, minSize=(30, 30), flags = cv.CV_HAAR_SCALE_IMAGE) 65 | 66 | return bBoxes 67 | 68 | def train_model(path): 69 | ''' 70 | Takes path to images and train a face recognition model 71 | Returns trained model and people 72 | ''' 73 | [images, labels, people]= get_images(sys.argv[1], (256, 256)) 74 | #print([images, labels]) 75 | 76 | labels= np.asarray(labels, dtype= np.int32) 77 | 78 | # initializing eigen_model and training 79 | print("Initializing eigen FaceRecognizer and training...") 80 | sttime= time.clock() 81 | eigen_model= cv2.createEigenFaceRecognizer() 82 | eigen_model.train(images, labels) 83 | print("\tSuccessfully completed training in "+ str(time.clock()- sttime)+ " Secs!") 84 | 85 | return [eigen_model, people] 86 | 87 | def majority(mylist): 88 | ''' 89 | Takes a list and returns an element which has highest frequency in the given list. 90 | ''' 91 | myset= set(mylist) 92 | ans= mylist[0] 93 | ans_f= mylist.count(ans) 94 | 95 | for i in myset: 96 | if mylist.count(i)> ans_f: 97 | ans= i 98 | ans_f= mylist.count(i) 99 | 100 | return ans 101 | 102 | def post_on_facebook(intruder, counter, picture_name): 103 | ''' 104 | Takes name of intruder and posts on your facebok timeline. 105 | You need to get access_token from facebook GraphAPI and paste it below. 106 | ''' 107 | # has a life time of 1 hr. So, no use even if you steal this 😜 108 | token= "CAACEdEose0cBAPr3Hjm3zudDaDg0CHZBbWj9TBKyBJH6NSXkNYT9nCqvMnp5rdjjBStMkt8aiicc22tyZBs5wb8g4jZCg2wfoBQUc8C7p38VoZBQWRgbZAZCQ8MDjeBFZBxvs5Ex0X0QhKor3ZAJMZBvjWXFx0Rdd6lDdhuwvfZCeaKRbM4kTyXbZCwHpXmsj6kX4bJ1ZA5JDMZBdLXJYeV9Bl1zM" 109 | url= "https://graph.facebook.com/me/feed" 110 | 111 | graph= facebook.GraphAPI(access_token= token) 112 | 113 | my_message1= "Surya is not in his room at present and '"+ intruder+ "' entered into his room without permission." 114 | my_message2= "PS: This is automatically posted by 'intruder alert system' built by Surya!\n" 115 | final_message= my_message1+"\n\n"+my_message2+ "\n"+ str(counter) 116 | 117 | #post on facebook using requests. 118 | # params= {"access_token": token, "message": final_message} 119 | # posted= requests.post(url, params) 120 | 121 | # if str(posted)== "": 122 | # print("\tSuccessfully posted on your timeline.") 123 | # else: 124 | # print("\tPlease check your token and its permissions.") 125 | # print("\tYou cannot post same message more than once in a single POST request.") 126 | 127 | #post on facebook using python GraphAPI 128 | graph.put_photo(image= open(picture_name), message= final_message) 129 | 130 | 131 | 132 | if __name__== "__main__": 133 | if len(sys.argv)!= 2: 134 | print("Wrong number of arguments! See the usage.\n") 135 | print("Usage: face_detrec_video.py ") 136 | sys.exit() 137 | 138 | arg_one= sys.argv[1] 139 | eigen_model, people= train_model(arg_one) 140 | 141 | #starts recording video from camera and detects & predict subjects 142 | cap= cv2.VideoCapture(0) 143 | 144 | counter= 0 145 | last_20= [0 for i in range(20)] 146 | final_5= [] 147 | box_text= "Subject: " 148 | 149 | while(True): 150 | ret, frame= cap.read() 151 | gray_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) 152 | gray_frame = cv2.equalizeHist(gray_frame) 153 | 154 | bBoxes= detect_faces(gray_frame) 155 | 156 | for bBox in bBoxes: 157 | (p,q,r,s)= bBox 158 | cv2.rectangle(frame, (p,q), (p+r,q+s), (225,0,25), 2) 159 | 160 | crop_gray_frame= gray_frame[q:q+s, p:p+r] 161 | crop_gray_frame= cv2.resize(crop_gray_frame, (256, 256)) 162 | 163 | [predicted_label, predicted_conf]= eigen_model.predict(np.asarray(crop_gray_frame)) 164 | last_20.append(predicted_label) 165 | last_20= last_20[1:] 166 | 167 | ''' 168 | counter modulo x: changes value of final label for every x frames 169 | Use max_label or predicted_label as you wish to see in the output video. 170 | But, posting on facebook always use max_label as a parameter. 171 | ''' 172 | 173 | cv2.putText(frame, box_text, (p-20, q-5), cv2.FONT_HERSHEY_PLAIN, 1.3, (25,0,225), 2) 174 | 175 | if counter%10== 0: 176 | max_label= majority(last_20) 177 | #box_text= format("Subject: "+ people[max_label]) 178 | box_text= format("Subject: "+ people[predicted_label]) 179 | 180 | if counter> 20: 181 | print("Will post on facebook timeline if this counter reaches to 5: "+ str(len(final_5)+ 1)) 182 | final_5.append(max_label) #it always takes max_label into consideration 183 | if len(final_5)== 5: 184 | final_label= majority(final_5) 185 | print("Intruder is "+ people[final_label]) 186 | print("Posting on your facebook timeline...") 187 | picture_name= "frame.jpg" 188 | cv2.imwrite(picture_name, frame) 189 | post_on_facebook(people[final_label], counter, picture_name) 190 | final_5= [] 191 | 192 | 193 | 194 | 195 | cv2.imshow("Video Window", frame) 196 | counter+= 1 197 | 198 | if (cv2.waitKey(5) & 0xFF== 27): 199 | break 200 | 201 | cv2.destroyAllWindows() 202 | -------------------------------------------------------------------------------- /face_recognition.py: -------------------------------------------------------------------------------- 1 | ''' 2 | Surya Teja Cheedella 3 | shine123surya[at]gmail[dot]com 4 | BITS Pilani, Hyderabad Campus 5 | 6 | Usage: face_recognition.py 7 | Takes two arguments: 8 | 1. Input folder which contains sub-folders of subjects/ persons. 9 | There should be images saved in subfolders which are used to train. 10 | 2. Path to a folder consists of images for which we are gonna predict subject. 11 | Note: Images in here should be cropped and have only faces of subjects. 12 | ''' 13 | 14 | import cv2 15 | import numpy as np 16 | from os import listdir 17 | import sys, time 18 | 19 | def get_images(path, size): 20 | ''' 21 | path: path to a folder which contains subfolders of for each subject/person 22 | which in turn cotains pictures of subjects/persons. 23 | 24 | size: a tuple to resize images. 25 | Ex- (256, 256) 26 | ''' 27 | sub= 0 28 | images, labels= [], [] 29 | people= [] 30 | 31 | for subdir in listdir(path): 32 | for image in listdir(path+ "/"+ subdir): 33 | #print(subdir, images) 34 | img= cv2.imread(path+"/"+subdir+"/"+image, cv2.IMREAD_GRAYSCALE) 35 | img= cv2.resize(img, size) 36 | 37 | images.append(np.asarray(img, dtype= np.uint8)) 38 | labels.append(sub) 39 | 40 | #cv2.imshow("win", img) 41 | #cv2.waitKey(10) 42 | 43 | people.append(subdir) 44 | sub+= 1 45 | 46 | return [images, labels, people] 47 | 48 | 49 | 50 | if __name__== "__main__": 51 | if len(sys.argv)!= 3: 52 | print("Wrong number of arguments! See the usage.\n") 53 | print("Usage: face_recognition.py ") 54 | sys.exit() 55 | 56 | [images, labels, people]= get_images(sys.argv[1], (256, 256)) 57 | #print([images, labels]) 58 | 59 | labels= np.asarray(labels, dtype= np.int32) 60 | 61 | # initializing eigen_model and training 62 | print("Initializing eigen FaceRecognizer and training...") 63 | sttime= time.clock() 64 | eigen_model= cv2.createEigenFaceRecognizer() 65 | eigen_model.train(images, labels) 66 | print("\tSuccessfully completed training in "+ str(time.clock()- sttime)+ " Secs!") 67 | 68 | # starting to predict subject/ person 69 | for image_name in listdir(sys.argv[2]): 70 | try: 71 | pre_image= cv2.imread(sys.argv[2]+ "/"+ image_name, cv2.IMREAD_GRAYSCALE) 72 | pre_image= cv2.resize(pre_image, (256, 256)) 73 | except: 74 | print("Couldn't read image. Please check the path to image file.") 75 | sys.exit() 76 | 77 | [predicted_label, predicted_conf]= eigen_model.predict(np.asarray(pre_image)) 78 | print("Predicted person in the image "+ image_name+ " : "+ people[predicted_label]) 79 | -------------------------------------------------------------------------------- /input_images/IMG_1037.JPG: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SnShine/FaceRecognizer/0db07cb6ea45f52d8aa2daf42b885a0626aee8f3/input_images/IMG_1037.JPG -------------------------------------------------------------------------------- /input_images/IMG_1038.JPG: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SnShine/FaceRecognizer/0db07cb6ea45f52d8aa2daf42b885a0626aee8f3/input_images/IMG_1038.JPG -------------------------------------------------------------------------------- /input_images/IMG_1039.JPG: 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-------------------------------------------------------------------------------- 1 | ''' 2 | Surya Teja Cheedella 3 | shine123surya[at]gmail[dot]com 4 | BITS Pilani, Hyderabad Campus 5 | 6 | Takes all the images in "input_path" and rotates & resizes them with given parameters. 7 | Modified images are saved at "output_path". 8 | ''' 9 | 10 | import cv2 11 | from os import listdir 12 | 13 | input_path= "input_images/" 14 | output_path= "new_resize/" 15 | 16 | images= listdir("/home/suryateja/Documents/GitHub/FaceRecognizer/"+ input_path) 17 | 18 | for image in images: 19 | print(input_path+ image) 20 | img= cv2.imread(input_path+ image) 21 | resize_img= cv2.resize(img, (650, 490)) 22 | 23 | (h, w)= resize_img.shape[:2] 24 | center= (w/2, h/2) 25 | 26 | matrix= cv2.getRotationMatrix2D(center, 270, 0.8) 27 | rotated_img = cv2.warpAffine(resize_img, matrix, (w, h)) 28 | 29 | cv2.imwrite(output_path+ image, rotated_img) 30 | cv2.imshow("Win", rotated_img) 31 | cv2.waitKey(5) 32 | 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