/
evaluate_streams.py
executable file
·55 lines (44 loc) · 2.45 KB
/
evaluate_streams.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
"""
********************************
* Created by mohammed-alaa *
********************************
Evaluate motion and spatial streams
"""
import frame_dataloader
from evaluation import legacy_load_model, get_batch_size
from evaluation.evaluation import *
from utils.drive_manager import DriveManager
"""
Evaluate spatial stream
"""
# download
drive_manager = DriveManager("spa-xception-adam-5e-06-imnet")
drive_manager.download_file('1djGzpxAYFvNX-UaQ7ONqDHGgnzc8clBK', "spatial.zip")
# load into ram
print("Spatial stream")
spatial_model_restored = legacy_load_model(filepath="spatial.h5", custom_objects={'sparse_categorical_cross_entropy_loss': sparse_categorical_cross_entropy_loss, "acc_top_1": acc_top_1, "acc_top_5": acc_top_5})
spatial_model_restored.summary()
# evaluate
_, spatial_test_loader, test_video_level_label = frame_dataloader.SpatialDataLoader(
width=int(spatial_model_restored.inputs[0].shape[1]), height=int(spatial_model_restored.inputs[0].shape[2]), batch_size=get_batch_size(spatial_model_restored, spatial=True), testing_samples_per_video=19
).run()
video_level_loss, video_level_accuracy_1, video_level_accuracy_5, test_video_level_preds = eval_model(spatial_model_restored, spatial_test_loader, test_video_level_label, 19)
print("Spatial Model validation", "prec@1", video_level_accuracy_1, "prec@5", video_level_accuracy_5, "loss", video_level_loss)
"""
Evaluate motion stream
"""
# download
drive_manager = DriveManager("heavy-mot-xception-adam-1e-05-imnet")
drive_manager.download_file('1kvslNL8zmZYaHRmhgAM6-l_pNDDA0EKZ', "motion.zip") # the id of the zip file contains my network
# load into ram
print("Motion stream")
motion_model_restored = legacy_load_model(filepath="motion.h5", custom_objects={'sparse_categorical_cross_entropy_loss': sparse_categorical_cross_entropy_loss, "acc_top_1": acc_top_1, "acc_top_5": acc_top_5})
motion_model_restored.summary()
# evaluate
_, motion_test_loader, test_video_level_label = frame_dataloader.MotionDataLoader(
width=int(motion_model_restored.inputs[0].shape[1]), height=int(motion_model_restored.inputs[0].shape[2])
,
batch_size=get_batch_size(motion_model_restored, spatial=True)
, testing_samples_per_video=19).run()
video_level_loss, video_level_accuracy_1, video_level_accuracy_5, _ = eval_model(motion_model_restored, motion_test_loader, test_video_level_label, 19)
print("Motion Model validation", "prec@1", video_level_accuracy_1, "prec@5", video_level_accuracy_5, "loss", video_level_loss)