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5 | 5 | import os
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6 | 6 | import datetime
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7 | 7 | import math
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| 8 | +import imutils |
8 | 9 | from libfaceid.detector import FaceDetectorModels, FaceDetector
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9 | 10 | from libfaceid.encoder import FaceEncoderModels, FaceEncoder
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10 | 11 | from libfaceid.classifier import FaceClassifierModels
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@@ -109,7 +110,8 @@ def process_faceenrollment(model_detector, cam_index, cam_resolution):
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109 | 110 | saveVideo = False
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110 | 111 | out = None
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111 | 112 | color_recording = (255,255,255)
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112 |
| - |
| 113 | + is_windows = (os.name == 'nt') |
| 114 | + |
113 | 115 |
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114 | 116 | while (True):
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115 | 117 |
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@@ -143,6 +145,8 @@ def process_faceenrollment(model_detector, cam_index, cam_resolution):
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143 | 145 | cv2.line(fg, (s1[i,0], s1[i,1]), (s2[i,0], s2[i,1]), (0, 0, 0), 2, cv2.LINE_AA)
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144 | 146 |
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145 | 147 | # Display updated frame
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| 148 | + if is_windows: |
| 149 | + fg = imutils.resize(fg, height=480) |
146 | 150 | cv2.imshow(WINDOW_NAME, fg)
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147 | 151 |
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148 | 152 | # Check for user actions
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@@ -216,8 +220,9 @@ def run(cam_index, cam_resolution, name):
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216 | 220 |
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217 | 221 | print("")
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218 | 222 | print("Processing of video recording started...")
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219 |
| - video_to_images(detector, "x" + INPUT_DIR_DATASET, name) |
220 |
| - video_to_images(detector, INPUT_DIR_DATASET, name, one_image_only=True) |
| 223 | +# video_to_images(detector, "x" + INPUT_DIR_DATASET, name) |
| 224 | +# video_to_images(detector, INPUT_DIR_DATASET, name, one_image_only=True) |
| 225 | + video_to_images(detector, INPUT_DIR_DATASET, name) |
221 | 226 | print("Processing of video recording completed!")
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222 | 227 | print("Make sure to train the new datasets before testing!")
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223 | 228 | print("")
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@@ -245,8 +250,9 @@ def main(args):
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245 | 250 |
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246 | 251 | print("")
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247 | 252 | print("Processing of video recording started...")
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248 |
| - video_to_images(detector, "x" + INPUT_DIR_DATASET, name) |
249 |
| - video_to_images(detector, INPUT_DIR_DATASET, name, one_image_only=True) |
| 253 | + #video_to_images(detector, "x" + INPUT_DIR_DATASET, name) |
| 254 | + #video_to_images(detector, INPUT_DIR_DATASET, name, one_image_only=True) |
| 255 | + video_to_images(detector, INPUT_DIR_DATASET, name) |
250 | 256 | print("Processing of video recording completed!")
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251 | 257 | print("Make sure to train the new datasets before testing!")
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252 | 258 | print("")
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