| | |
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| | | |
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| | | # ResNet50 with 3 outputs. |
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| | | model = hopenet.Hopenet(torchvision.models.resnet.Bottleneck, [3, 4, 6, 3], 66) |
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| | | # model = hopenet.Hopenet(torchvision.models.resnet.BasicBlock, [2, 2, 2, 2], 66) |
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| | | |
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| | | print 'Loading snapshot.' |
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| | | # Load snapshot |
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| | |
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| | | pitch_error += abs(pitch_predicted - label_pitch[0]) * 3 |
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| | | roll_error += abs(roll_predicted - label_roll[0]) * 3 |
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| | | |
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| | | # print yaw_predicted * 3, label_yaw[0] * 3, abs(yaw_predicted - label_yaw[0]) * 3 |
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| | | |
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| | | # for er in xrange(0,n_margins): |
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| | | # yaw_correct[er] += (label_yaw[0] in range(yaw_predicted[0,0] - er, yaw_predicted[0,0] + er + 1)) |
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| | | # pitch_correct[er] += (label_pitch[0] in range(pitch_predicted[0,0] - er, pitch_predicted[0,0] + er + 1)) |
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