xref: /aosp_15_r20/external/armnn/python/pyarmnn/examples/tests/test_style_transfer.py (revision 89c4ff92f2867872bb9e2354d150bf0c8c502810) 
1# Copyright © 2022 Arm Ltd and Contributors. All rights reserved.
2# SPDX-License-Identifier: MIT
3
4import os
5import cv2
6import numpy as np
7
8from context import style_transfer
9from context import cv_utils
10
11
12def test_style_transfer_postprocess(test_data_folder):
13    content_image = "messi5.jpg"
14    target_shape = (1,256,256,3)
15    keep_aspect_ratio = False
16    image = cv2.imread(os.path.join(test_data_folder, content_image))
17    original_shape = image.shape
18    preprocessed_image = cv_utils.preprocess(image, np.float32, target_shape, False, keep_aspect_ratio)
19    assert preprocessed_image.shape == target_shape
20
21    postprocess_image = style_transfer.style_transfer_postprocess(preprocessed_image, original_shape)
22    assert postprocess_image.shape == original_shape
23
24
25def test_style_transfer(test_data_folder):
26    style_predict_model_path = os.path.join(test_data_folder, "style_predict.tflite")
27    style_transfer_model_path = os.path.join(test_data_folder, "style_transfer.tflite")
28    backends = ["CpuAcc", "CpuRef"]
29    delegate_path = os.path.join(test_data_folder, "libarmnnDelegate.so")
30    image = cv2.imread(os.path.join(test_data_folder, "messi5.jpg"))
31
32    style_transfer_executor = style_transfer.StyleTransfer(style_predict_model_path, style_transfer_model_path,
33                                                           image, backends, delegate_path)
34
35    assert style_transfer_executor.get_style_predict_executor_shape() == (1, 256, 256, 3)
36
37def test_run_style_transfer(test_data_folder):
38    style_predict_model_path = os.path.join(test_data_folder, "style_predict.tflite")
39    style_transfer_model_path = os.path.join(test_data_folder, "style_transfer.tflite")
40    backends = ["CpuAcc", "CpuRef"]
41    delegate_path = os.path.join(test_data_folder, "libarmnnDelegate.so")
42    style_image = cv2.imread(os.path.join(test_data_folder, "messi5.jpg"))
43    content_image = cv2.imread(os.path.join(test_data_folder, "basketball1.png"))
44
45    style_transfer_executor = style_transfer.StyleTransfer(style_predict_model_path, style_transfer_model_path,
46                                                           style_image, backends, delegate_path)
47
48    stylized_image = style_transfer_executor.run_style_transfer(content_image)
49    assert stylized_image.shape == content_image.shape
50
51
52def test_create_stylized_detection(test_data_folder):
53    style_predict_model_path = os.path.join(test_data_folder, "style_predict.tflite")
54    style_transfer_model_path = os.path.join(test_data_folder, "style_transfer.tflite")
55    backends = ["CpuAcc", "CpuRef"]
56    delegate_path = os.path.join(test_data_folder, "libarmnnDelegate.so")
57
58    style_image = cv2.imread(os.path.join(test_data_folder, "messi5.jpg"))
59    content_image = cv2.imread(os.path.join(test_data_folder, "basketball1.png"))
60    detections = [(0.0, [0.16745174, 0.15101701, 0.5371381, 0.74165875], 0.87597656)]
61    labels = {0: ('person', (50.888902345757494, 129.61878417939724, 207.2891028294508)),
62             1: ('bicycle', (55.055339686943654, 55.828708219750574, 43.550389695374676)),
63             2: ('car', (95.33096265662336, 194.872841553212, 218.58516479057758))}
64    style_transfer_executor = style_transfer.StyleTransfer(style_predict_model_path, style_transfer_model_path,
65                                                           style_image, backends, delegate_path)
66
67    stylized_image = style_transfer.create_stylized_detection(style_transfer_executor, 'person', content_image,
68                                                              detections, 720, labels)
69
70    assert stylized_image.shape == content_image.shape
71