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Refactor transforms and add transforms/functional.py #311

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50 changes: 25 additions & 25 deletions test/test_transforms.py
Original file line number Diff line number Diff line change
@@ -1,5 +1,6 @@
import torch
import torchvision.transforms as transforms
import torchvision.transforms.functional as F
import unittest
import random
import numpy as np
Expand All @@ -14,7 +15,6 @@
except ImportError:
stats = None


GRACE_HOPPER = 'assets/grace_hopper_517x606.jpg'


Expand Down Expand Up @@ -347,7 +347,7 @@ def verify_img_data(img_data, expected_output, mode):
assert img.mode == mode
split = img.split()
for i in range(3):
assert np.allclose(expected_output[i].numpy(), transforms.to_tensor(split[i]).numpy())
assert np.allclose(expected_output[i].numpy(), F.to_tensor(split[i]).numpy())

img_data = torch.Tensor(3, 4, 4).uniform_()
expected_output = img_data.mul(255).int().float().div(255)
Expand Down Expand Up @@ -391,7 +391,7 @@ def verify_img_data(img_data, expected_output, mode):

split = img.split()
for i in range(4):
assert np.allclose(expected_output[i].numpy(), transforms.to_tensor(split[i]).numpy())
assert np.allclose(expected_output[i].numpy(), F.to_tensor(split[i]).numpy())

img_data = torch.Tensor(4, 4, 4).uniform_()
expected_output = img_data.mul(255).int().float().div(255)
Expand Down Expand Up @@ -491,19 +491,19 @@ def test_adjust_brightness(self):
x_pil = Image.fromarray(x_np, mode='RGB')

# test 0
y_pil = transforms.adjust_brightness(x_pil, 1)
y_pil = F.adjust_brightness(x_pil, 1)
y_np = np.array(y_pil)
assert np.allclose(y_np, x_np)

# test 1
y_pil = transforms.adjust_brightness(x_pil, 0.5)
y_pil = F.adjust_brightness(x_pil, 0.5)
y_np = np.array(y_pil)
y_ans = [0, 2, 6, 27, 67, 113, 18, 4, 117, 45, 127, 0]
y_ans = np.array(y_ans, dtype=np.uint8).reshape(x_shape)
assert np.allclose(y_np, y_ans)

# test 2
y_pil = transforms.adjust_brightness(x_pil, 2)
y_pil = F.adjust_brightness(x_pil, 2)
y_np = np.array(y_pil)
y_ans = [0, 10, 26, 108, 255, 255, 74, 16, 255, 180, 255, 2]
y_ans = np.array(y_ans, dtype=np.uint8).reshape(x_shape)
Expand All @@ -516,19 +516,19 @@ def test_adjust_contrast(self):
x_pil = Image.fromarray(x_np, mode='RGB')

# test 0
y_pil = transforms.adjust_contrast(x_pil, 1)
y_pil = F.adjust_contrast(x_pil, 1)
y_np = np.array(y_pil)
assert np.allclose(y_np, x_np)

# test 1
y_pil = transforms.adjust_contrast(x_pil, 0.5)
y_pil = F.adjust_contrast(x_pil, 0.5)
y_np = np.array(y_pil)
y_ans = [43, 45, 49, 70, 110, 156, 61, 47, 160, 88, 170, 43]
y_ans = np.array(y_ans, dtype=np.uint8).reshape(x_shape)
assert np.allclose(y_np, y_ans)

# test 2
y_pil = transforms.adjust_contrast(x_pil, 2)
y_pil = F.adjust_contrast(x_pil, 2)
y_np = np.array(y_pil)
y_ans = [0, 0, 0, 22, 184, 255, 0, 0, 255, 94, 255, 0]
y_ans = np.array(y_ans, dtype=np.uint8).reshape(x_shape)
Expand All @@ -541,19 +541,19 @@ def test_adjust_saturation(self):
x_pil = Image.fromarray(x_np, mode='RGB')

# test 0
y_pil = transforms.adjust_saturation(x_pil, 1)
y_pil = F.adjust_saturation(x_pil, 1)
y_np = np.array(y_pil)
assert np.allclose(y_np, x_np)

# test 1
y_pil = transforms.adjust_saturation(x_pil, 0.5)
y_pil = F.adjust_saturation(x_pil, 0.5)
y_np = np.array(y_pil)
y_ans = [2, 4, 8, 87, 128, 173, 39, 25, 138, 133, 215, 88]
y_ans = np.array(y_ans, dtype=np.uint8).reshape(x_shape)
assert np.allclose(y_np, y_ans)

# test 2
y_pil = transforms.adjust_saturation(x_pil, 2)
y_pil = F.adjust_saturation(x_pil, 2)
y_np = np.array(y_pil)
y_ans = [0, 6, 22, 0, 149, 255, 32, 0, 255, 4, 255, 0]
y_ans = np.array(y_ans, dtype=np.uint8).reshape(x_shape)
Expand All @@ -566,26 +566,26 @@ def test_adjust_hue(self):
x_pil = Image.fromarray(x_np, mode='RGB')

with self.assertRaises(ValueError):
transforms.adjust_hue(x_pil, -0.7)
transforms.adjust_hue(x_pil, 1)
F.adjust_hue(x_pil, -0.7)
F.adjust_hue(x_pil, 1)

# test 0: almost same as x_data but not exact.
# probably because hsv <-> rgb floating point ops
y_pil = transforms.adjust_hue(x_pil, 0)
y_pil = F.adjust_hue(x_pil, 0)
y_np = np.array(y_pil)
y_ans = [0, 5, 13, 54, 139, 226, 35, 8, 234, 91, 255, 1]
y_ans = np.array(y_ans, dtype=np.uint8).reshape(x_shape)
assert np.allclose(y_np, y_ans)

# test 1
y_pil = transforms.adjust_hue(x_pil, 0.25)
y_pil = F.adjust_hue(x_pil, 0.25)
y_np = np.array(y_pil)
y_ans = [13, 0, 12, 224, 54, 226, 234, 8, 99, 1, 222, 255]
y_ans = np.array(y_ans, dtype=np.uint8).reshape(x_shape)
assert np.allclose(y_np, y_ans)

# test 2
y_pil = transforms.adjust_hue(x_pil, -0.25)
y_pil = F.adjust_hue(x_pil, -0.25)
y_np = np.array(y_pil)
y_ans = [0, 13, 2, 54, 226, 58, 8, 234, 152, 255, 43, 1]
y_ans = np.array(y_ans, dtype=np.uint8).reshape(x_shape)
Expand All @@ -598,19 +598,19 @@ def test_adjust_gamma(self):
x_pil = Image.fromarray(x_np, mode='RGB')

# test 0
y_pil = transforms.adjust_gamma(x_pil, 1)
y_pil = F.adjust_gamma(x_pil, 1)
y_np = np.array(y_pil)
assert np.allclose(y_np, x_np)

# test 1
y_pil = transforms.adjust_gamma(x_pil, 0.5)
y_pil = F.adjust_gamma(x_pil, 0.5)
y_np = np.array(y_pil)
y_ans = [0, 35, 57, 117, 185, 240, 97, 45, 244, 151, 255, 15]
y_ans = np.array(y_ans, dtype=np.uint8).reshape(x_shape)
assert np.allclose(y_np, y_ans)

# test 2
y_pil = transforms.adjust_gamma(x_pil, 2)
y_pil = F.adjust_gamma(x_pil, 2)
y_np = np.array(y_pil)
y_ans = [0, 0, 0, 11, 71, 200, 5, 0, 214, 31, 255, 0]
y_ans = np.array(y_ans, dtype=np.uint8).reshape(x_shape)
Expand All @@ -623,11 +623,11 @@ def test_adjusts_L_mode(self):
x_rgb = Image.fromarray(x_np, mode='RGB')

x_l = x_rgb.convert('L')
assert transforms.adjust_brightness(x_l, 2).mode == 'L'
assert transforms.adjust_saturation(x_l, 2).mode == 'L'
assert transforms.adjust_contrast(x_l, 2).mode == 'L'
assert transforms.adjust_hue(x_l, 0.4).mode == 'L'
assert transforms.adjust_gamma(x_l, 0.5).mode == 'L'
assert F.adjust_brightness(x_l, 2).mode == 'L'
assert F.adjust_saturation(x_l, 2).mode == 'L'
assert F.adjust_contrast(x_l, 2).mode == 'L'
assert F.adjust_hue(x_l, 0.4).mode == 'L'
assert F.adjust_gamma(x_l, 0.5).mode == 'L'

def test_color_jitter(self):
color_jitter = transforms.ColorJitter(2, 2, 2, 0.1)
Expand Down
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