Python PIL.Image.merge() Examples
The following are 30
code examples of PIL.Image.merge().
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Example #1
| Source File: super_resolution.py From dynamic-training-with-apache-mxnet-on-aws with Apache License 2.0 | 6 votes |
|
def resolve(ctx):
from PIL import Image
if isinstance(ctx, list):
ctx = [ctx[0]]
net.load_parameters('superres.params', ctx=ctx)
img = Image.open(opt.resolve_img).convert('YCbCr')
y, cb, cr = img.split()
data = mx.nd.expand_dims(mx.nd.expand_dims(mx.nd.array(y), axis=0), axis=0)
out_img_y = mx.nd.reshape(net(data), shape=(-3, -2)).asnumpy()
out_img_y = out_img_y.clip(0, 255)
out_img_y = Image.fromarray(np.uint8(out_img_y[0]), mode='L')
out_img_cb = cb.resize(out_img_y.size, Image.BICUBIC)
out_img_cr = cr.resize(out_img_y.size, Image.BICUBIC)
out_img = Image.merge('YCbCr', [out_img_y, out_img_cb, out_img_cr]).convert('RGB')
out_img.save('resolved.png')
Example #2
| Source File: utils.py From emotion_classification with MIT License | 6 votes |
|
def distort_image(im, hue, sat, val):
im = im.convert('HSV')
cs = list(im.split())
cs[1] = cs[1].point(lambda i: i * sat)
cs[2] = cs[2].point(lambda i: i * val)
def change_hue(x):
x += hue*255
if x > 255:
x -= 255
if x < 0:
x += 255
return x
cs[0] = cs[0].point(change_hue)
im = Image.merge(im.mode, tuple(cs))
im = im.convert('RGB')
return im
Example #3
| Source File: utils.py From emotion_classification with MIT License | 6 votes |
|
def distort_image(im, hue, sat, val):
im = im.convert('HSV')
cs = list(im.split())
cs[1] = cs[1].point(lambda i: i * sat)
cs[2] = cs[2].point(lambda i: i * val)
def change_hue(x):
x += hue*255
if x > 255:
x -= 255
if x < 0:
x += 255
return x
cs[0] = cs[0].point(change_hue)
im = Image.merge(im.mode, tuple(cs))
im = im.convert('RGB')
return im
Example #4
| Source File: image.py From pytorch-0.4-yolov3 with MIT License | 6 votes |
|
def distort_image(im, hue, sat, val):
im = im.convert('HSV')
cs = list(im.split())
cs[1] = cs[1].point(lambda i: i * sat)
cs[2] = cs[2].point(lambda i: i * val)
def change_hue(x):
x += hue*255
if x > 255:
x -= 255
if x < 0:
x += 255
return x
cs[0] = cs[0].point(change_hue)
im = Image.merge(im.mode, tuple(cs))
im = im.convert('RGB')
#constrain_image(im)
return im
Example #5
| Source File: key.py From kle_render with MIT License | 6 votes |
|
def open_base_img(full_profile, res, base_color, color):
# get base image according to profile and perceptual gray of key color
base_num = str([0xE0, 0xB0, 0x80, 0x50, 0x20].index(base_color) + 1)
# open image and convert to Lab
with Image.open('images/{0}_{1}{2}.png'.format(*full_profile, base_num)) as img:
key_img = img.resize((int(s * res / 200) for s in img.size), resample=Image.BILINEAR).convert('RGBA')
if full_profile[1] in ('ISO', 'BIGENTER'): alpha = key_img.split()[-1]
l, a, b = ImageCms.applyTransform(key_img, rgb2lab_transform).split()
# convert key color to Lab
# a and b should be scaled by 128/100, but desaturation looks more natural
rgb_color = color_objects.sRGBColor(*ImageColor.getrgb(color), is_upscaled=True)
lab_color = color_conversions.convert_color(rgb_color, color_objects.LabColor)
l1, a1, b1 = lab_color.get_value_tuple()
l1, a1, b1 = int(l1 * 256 / 100), int(a1 + 128), int(b1 + 128)
# change Lab of base image to match that of key color
l = ImageMath.eval('convert(l + l1 - l_avg, "L")', l=l, l1=l1, l_avg=base_color)
a = ImageMath.eval('convert(a + a1 - a, "L")', a=a, a1=a1)
b = ImageMath.eval('convert(b + b1 - b, "L")', b=b, b1=b1)
key_img = ImageCms.applyTransform(Image.merge('LAB', (l, a, b)), lab2rgb_transform).convert('RGBA')
if full_profile[1] in ('ISO', 'BIGENTER'): key_img.putalpha(alpha)
return key_img
Example #6
| Source File: loader.py From 3D-ResNets-PyTorch with MIT License | 6 votes |
|
def __call__(self, video_path, frame_indices):
with h5py.File(video_path, 'r') as f:
flow_data = []
for flow in self.flows:
flow_data.append(f[f'video_{flow}'])
video = []
for i in frame_indices:
if i < len(flow_data[0]):
frame = [
Image.open(io.BytesIO(video_data[i]))
for video_data in flow_data
]
frame.append(frame[-1]) # add dummy data into third channel
video.append(Image.merge('RGB', frame))
return video
Example #7
| Source File: super_resolution.py From training_results_v0.6 with Apache License 2.0 | 6 votes |
|
def resolve(ctx):
from PIL import Image
if isinstance(ctx, list):
ctx = [ctx[0]]
net.load_parameters('superres.params', ctx=ctx)
img = Image.open(opt.resolve_img).convert('YCbCr')
y, cb, cr = img.split()
data = mx.nd.expand_dims(mx.nd.expand_dims(mx.nd.array(y), axis=0), axis=0)
out_img_y = mx.nd.reshape(net(data), shape=(-3, -2)).asnumpy()
out_img_y = out_img_y.clip(0, 255)
out_img_y = Image.fromarray(np.uint8(out_img_y[0]), mode='L')
out_img_cb = cb.resize(out_img_y.size, Image.BICUBIC)
out_img_cr = cr.resize(out_img_y.size, Image.BICUBIC)
out_img = Image.merge('YCbCr', [out_img_y, out_img_cb, out_img_cr]).convert('RGB')
out_img.save('resolved.png')
Example #8
| Source File: test_image_filter.py From python3_ios with BSD 3-Clause "New" or "Revised" License | 6 votes |
|
def test_consistency_5x5(self):
source = Image.open("Tests/images/hopper.bmp")
reference = Image.open("Tests/images/hopper_emboss_more.bmp")
kernel = ImageFilter.Kernel((5, 5), # noqa: E127
(-1, -1, -1, -1, 0,
-1, -1, -1, 0, 1,
-1, -1, 0, 1, 1,
-1, 0, 1, 1, 1,
0, 1, 1, 1, 1), 0.3)
source = source.split() * 2
reference = reference.split() * 2
for mode in ['L', 'LA', 'RGB', 'CMYK']:
self.assert_image_equal(
Image.merge(mode, source[:len(mode)]).filter(kernel),
Image.merge(mode, reference[:len(mode)]),
)
Example #9
| Source File: test_color_lut.py From python3_ios with BSD 3-Clause "New" or "Revised" License | 6 votes |
|
def test_channels_order(self):
g = Image.linear_gradient('L')
im = Image.merge('RGB', [g, g.transpose(Image.ROTATE_90),
g.transpose(Image.ROTATE_180)])
# Reverse channels by splitting and using table
self.assert_image_equal(
Image.merge('RGB', im.split()[::-1]),
im._new(im.im.color_lut_3d('RGB', Image.LINEAR,
3, 2, 2, 2, [
0, 0, 0, 0, 0, 1,
0, 1, 0, 0, 1, 1,
1, 0, 0, 1, 0, 1,
1, 1, 0, 1, 1, 1,
])))
Example #10
| Source File: test_format_hsv.py From python3_ios with BSD 3-Clause "New" or "Revised" License | 6 votes |
|
def wedge(self):
w = Image._wedge()
w90 = w.rotate(90)
(px, h) = w.size
r = Image.new('L', (px*3, h))
g = r.copy()
b = r.copy()
r.paste(w, (0, 0))
r.paste(w90, (px, 0))
g.paste(w90, (0, 0))
g.paste(w, (2*px, 0))
b.paste(w, (px, 0))
b.paste(w90, (2*px, 0))
img = Image.merge('RGB', (r, g, b))
return img
Example #11
| Source File: deepfry.py From FlameCogs with MIT License | 6 votes |
|
def _fry(img):
e = ImageEnhance.Sharpness(img)
img = e.enhance(100)
e = ImageEnhance.Contrast(img)
img = e.enhance(100)
e = ImageEnhance.Brightness(img)
img = e.enhance(.27)
r, b, g = img.split()
e = ImageEnhance.Brightness(r)
r = e.enhance(4)
e = ImageEnhance.Brightness(g)
g = e.enhance(1.75)
e = ImageEnhance.Brightness(b)
b = e.enhance(.6)
img = Image.merge('RGB', (r, g, b))
e = ImageEnhance.Brightness(img)
img = e.enhance(1.5)
temp = BytesIO()
temp.name = 'deepfried.png'
img.save(temp)
temp.seek(0)
return temp
Example #12
| Source File: sensor.py From coiltraine with MIT License | 6 votes |
|
def save_to_disk(self, filename, format='.png'):
"""Save this image to disk (requires PIL installed)."""
filename = _append_extension(filename, format)
try:
from PIL import Image as PImage
except ImportError:
raise RuntimeError(
'cannot import PIL, make sure pillow package is installed')
image = PImage.frombytes(
mode='RGBA',
size=(self.width, self.height),
data=self.raw_data,
decoder_name='raw')
color = image.split()
image = PImage.merge("RGB", color[2::-1])
folder = os.path.dirname(filename)
if not os.path.isdir(folder):
os.makedirs(folder)
image.save(filename, quality=100)
Example #13
| Source File: inference_with_net.py From TableTrainNet with MIT License | 6 votes |
|
def from_png_to_bmp(png_path, output_path=BMP_IMAGE_TEST_TO_PATH):
"""
Convert a png_path image into a bmp 3-channel one and return the path to the converted image
:param png_path: path of the image
:param output_path: path in which we save the image
:return: the file path
"""
# convert a .png image file to a .bmp image file using PIL
file_name = os.path.splitext(png_path)[0] \
.split("/")[-1]
file_in = png_path
img = Image.open(file_in)
file_out = os.path.join(output_path, str(file_name), str(file_name) + '.bmp')
len(img.split()) # test
if len(img.split()) == 4:
# prevent IOError: cannot write mode RGBA as BMP
r, g, b, a = img.split()
img = Image.merge("RGB", (r, g, b))
img.save(file_out)
else:
img.save(file_out)
return file_out
Example #14
| Source File: sensor.py From Hands-On-Intelligent-Agents-with-OpenAI-Gym with MIT License | 6 votes |
|
def save_to_disk(self, filename):
"""Save this image to disk (requires PIL installed)."""
filename = _append_extension(filename, '.png')
try:
from PIL import Image as PImage
except ImportError:
raise RuntimeError(
'cannot import PIL, make sure pillow package is installed')
image = PImage.frombytes(
mode='RGBA',
size=(self.width, self.height),
data=self.raw_data,
decoder_name='raw')
color = image.split()
image = PImage.merge("RGB", color[2::-1])
folder = os.path.dirname(filename)
if not os.path.isdir(folder):
os.makedirs(folder)
image.save(filename)
Example #15
| Source File: sensor.py From Hands-On-Intelligent-Agents-with-OpenAI-Gym with MIT License | 6 votes |
|
def save_to_disk(self, filename):
"""Save this image to disk (requires PIL installed)."""
filename = _append_extension(filename, '.png')
try:
from PIL import Image as PImage
except ImportError:
raise RuntimeError(
'cannot import PIL, make sure pillow package is installed')
image = PImage.frombytes(
mode='RGBA',
size=(self.width, self.height),
data=self.raw_data,
decoder_name='raw')
color = image.split()
image = PImage.merge("RGB", color[2::-1])
folder = os.path.dirname(filename)
if not os.path.isdir(folder):
os.makedirs(folder)
image.save(filename)
Example #16
| Source File: utils.py From YOLO with MIT License | 6 votes |
|
def distort_image(im, hue, sat, val):
im = im.convert('HSV')
cs = list(im.split())
cs[1] = cs[1].point(lambda i: i * sat)
cs[2] = cs[2].point(lambda i: i * val)
def change_hue(x):
x += hue*255
if x > 255:
x -= 255
if x < 0:
x += 255
return x
cs[0] = cs[0].point(change_hue)
im = Image.merge(im.mode, tuple(cs))
im = im.convert('RGB')
return im
# generate random scale.
Example #17
| Source File: super_resolution.py From dynamic-training-with-apache-mxnet-on-aws with Apache License 2.0 | 5 votes |
|
def perform_inference(sym, arg_params, aux_params, input_img, img_cb, img_cr):
"""Perform inference on image using mxnet"""
metadata = onnx_mxnet.get_model_metadata('super_resolution.onnx')
data_names = [input_name[0] for input_name in metadata.get('input_tensor_data')]
# create module
mod = mx.mod.Module(symbol=sym, data_names=data_names, label_names=None)
mod.bind(for_training=False, data_shapes=[(data_names[0], input_img.shape)])
mod.set_params(arg_params=arg_params, aux_params=aux_params)
# run inference
batch = namedtuple('Batch', ['data'])
mod.forward(batch([mx.nd.array(input_img)]))
# Save the result
img_out_y = Image.fromarray(np.uint8(mod.get_outputs()[0][0][0].
asnumpy().clip(0, 255)), mode='L')
result_img = Image.merge(
"YCbCr", [img_out_y,
img_cb.resize(img_out_y.size, Image.BICUBIC),
img_cr.resize(img_out_y.size, Image.BICUBIC)]).convert("RGB")
output_img_dim = 672
assert result_img.size == (output_img_dim, output_img_dim)
LOGGER.info("Super Resolution example success.")
result_img.save("super_res_output.jpg")
return result_img
Example #18
| Source File: playertoken.py From avrae with GNU General Public License v3.0 | 5 votes |
|
def color(src, target):
num_pixels = src.size[0] * src.size[1]
colors = src.getcolors(num_pixels)
rgb = sum(c[0] * c[1][0] for c in colors), sum(c[0] * c[1][1] for c in colors), sum(
c[0] * c[1][2] for c in colors)
rgb = rgb[0] / num_pixels, rgb[1] / num_pixels, rgb[2] / num_pixels
bands = target.split()
for i, v in enumerate(rgb):
out = bands[i].point(lambda p: int(p * v / 255))
bands[i].paste(out)
return Image.merge(target.mode, bands)
Example #19
| Source File: image.py From pytorch-0.4-yolov3 with MIT License | 5 votes |
|
def scale_image_channel(im, c, v):
cs = list(im.split())
cs[c] = cs[c].point(lambda i: i * v)
out = Image.merge(im.mode, tuple(cs))
return out
Example #20
| Source File: pil_utils.py From FastMaskRCNN with Apache License 2.0 | 5 votes |
|
def draw_bbox(step, image, name='', image_height=1, image_width=1, bbox=None, label=None, gt_label=None, prob=None):
#print(prob[:,label])
source_img = Image.fromarray(image)
b, g, r = source_img.split()
source_img = Image.merge("RGB", (r, g, b))
draw = ImageDraw.Draw(source_img)
color = '#0000ff'
if bbox is not None:
for i, box in enumerate(bbox):
if label is not None:
if prob is not None:
if (prob[i,label[i]] > 0.5) and (label[i] > 0):
if gt_label is not None:
text = cat_id_to_cls_name(label[i]) + ' : ' + cat_id_to_cls_name(gt_label[i])
if label[i] != gt_label[i]:
color = '#ff0000'#draw.text((2+bbox[i,0], 2+bbox[i,1]), cat_id_to_cls_name(label[i]) + ' : ' + cat_id_to_cls_name(gt_label[i]), fill='#ff0000')
else:
color = '#0000ff'
else:
text = cat_id_to_cls_name(label[i])
draw.text((2+bbox[i,0], 2+bbox[i,1]), text, fill=color)
if _DEBUG is True:
print("plot",label[i], prob[i,label[i]])
draw.rectangle(box,fill=None,outline=color)
else:
if _DEBUG is True:
print("skip",label[i], prob[i,label[i]])
else:
text = cat_id_to_cls_name(label[i])
draw.text((2+bbox[i,0], 2+bbox[i,1]), text, fill=color)
draw.rectangle(box,fill=None,outline=color)
return source_img.save(FLAGS.train_dir + '/est_imgs/test_' + name + '_' + str(step) +'.jpg', 'JPEG')
Example #21
| Source File: neural_style.py From neural-style-pt with MIT License | 5 votes |
|
def original_colors(content, generated):
content_channels = list(content.convert('YCbCr').split())
generated_channels = list(generated.convert('YCbCr').split())
content_channels[0] = generated_channels[0]
return Image.merge('YCbCr', content_channels).convert('RGB')
# Print like Lua/Torch7
Example #22
| Source File: multi_gpu.py From MoePhoto with Apache License 2.0 | 5 votes |
|
def multi_gpu_run(model, im_path, outpath, gpus):
print('running with multi GPU')
# 如果patch一样大，开这个会加速
cudnn.benchmark = True
# 输入2D Tensor=[Batch,Channel,H,W]
dataset = DatasetFromImage(im_path)
# 暂定一个GPU跑一张图
loader = DataLoader(dataset=dataset, batch_size=gpus)
trans = transforms.Compose([
transforms.ToPILImage(),
])
for iter, batch in enumerate(loader, 1):
y = batch[0]
bicubic = batch[1]
names = batch[2]
# print(y)
if torch.cuda.is_available():
y = y.cuda()
else:
y = y.cpu()
im_h_y = model(y)
print(im_h_y.shape)
#得看下shape，此处应该有个循环，把batch分解成多个图再合成
im_h_y = trans(im_h_y)
bicubic = trans(bicubic).convert("YCbCr")
y, cb, cr = bicubic.split()
HR = Image.merge('YCbCr', (im_h_y, cb, cr))
HR.save(outpath)
Example #23
| Source File: mpv.py From python-mpv with GNU Affero General Public License v3.0 | 5 votes |
|
def screenshot_raw(self, includes='subtitles'):
"""Mapped mpv screenshot_raw command, see man mpv(1). Returns a pillow Image object."""
from PIL import Image
res = self.node_command('screenshot-raw', includes)
if res['format'] != 'bgr0':
raise ValueError('Screenshot in unknown format "{}". Currently, only bgr0 is supported.'
.format(res['format']))
img = Image.frombytes('RGBA', (res['stride']//4, res['h']), res['data'])
b,g,r,a = img.split()
return Image.merge('RGB', (r,g,b))
Example #24
| Source File: coco_loader.py From sunets with MIT License | 5 votes |
|
def r_rotate(self, img, lbl):
angle = random.uniform(-10, 10)
lbl = np.array(lbl, dtype=np.int32) - self.ignore_index
lbl = Image.fromarray(lbl)
img = tuple([ImageMath.eval("int(a)-b", a=j, b=self.filler[i]) for i, j in enumerate(img.split())])
lbl = lbl.rotate(angle, resample=Image.NEAREST)
img = tuple([k.rotate(angle, resample=Image.BICUBIC) for k in img])
lbl = ImageMath.eval("int(a)+b", a=lbl, b=self.ignore_index)
img = Image.merge(mode='RGB', bands=tuple(
[ImageMath.eval("convert(int(a)+b,'L')", a=j, b=self.filler[i]) for i, j in enumerate(img)]))
return (img, lbl)
Example #25
| Source File: pascal_voc_loader.py From sunets with MIT License | 5 votes |
|
def r_rotate(self, img, lbl):
angle = random.uniform(-10, 10)
lbl = np.array(lbl, dtype=np.int32) - self.ignore_index
lbl = Image.fromarray(lbl)
img = tuple([ImageMath.eval("int(a)-b", a=j, b=self.filler[i]) for i, j in enumerate(img.split())])
lbl = lbl.rotate(angle, resample=Image.NEAREST)
img = tuple([k.rotate(angle, resample=Image.BICUBIC) for k in img])
lbl = ImageMath.eval("int(a)+b", a=lbl, b=self.ignore_index)
img = Image.merge(mode='RGB', bands=tuple(
[ImageMath.eval("convert(int(a)+b,'L')", a=j, b=self.filler[i]) for i, j in enumerate(img)]))
return (img, lbl)
Example #26
| Source File: mpv_bak.py From kawaii-player with GNU General Public License v3.0 | 5 votes |
|
def screenshot_raw(self, includes='subtitles'):
"""Mapped mpv screenshot_raw command, see man mpv(1). Returns a pillow Image object."""
from PIL import Image
res = self.node_command('screenshot-raw', includes)
if res['format'] != 'bgr0':
raise ValueError('Screenshot in unknown format "{}". Currently, only bgr0 is supported.'
.format(res['format']))
img = Image.frombytes('RGBA', (res['w'], res['h']), res['data'])
b,g,r,a = img.split()
return Image.merge('RGB', (r,g,b))
Example #27
| Source File: test_image_filter.py From python3_ios with BSD 3-Clause "New" or "Revised" License | 5 votes |
|
def test_consistency_3x3(self):
source = Image.open("Tests/images/hopper.bmp")
reference = Image.open("Tests/images/hopper_emboss.bmp")
kernel = ImageFilter.Kernel((3, 3), # noqa: E127
(-1, -1, 0,
-1, 0, 1,
0, 1, 1), .3)
source = source.split() * 2
reference = reference.split() * 2
for mode in ['L', 'LA', 'RGB', 'CMYK']:
self.assert_image_equal(
Image.merge(mode, source[:len(mode)]).filter(kernel),
Image.merge(mode, reference[:len(mode)]),
)
Example #28
| Source File: test_box_blur.py From python3_ios with BSD 3-Clause "New" or "Revised" License | 5 votes |
|
def assertBlur(self, im, radius, data, passes=1, delta=0):
# check grayscale image
self.assertImage(self.box_blur(im, radius, passes), data, delta)
rgba = Image.merge('RGBA', (im, im, im, im))
for band in self.box_blur(rgba, radius, passes).split():
self.assertImage(band, data, delta)
Example #29
| Source File: test_file_mic.py From python3_ios with BSD 3-Clause "New" or "Revised" License | 5 votes |
|
def test_sanity(self):
im = Image.open(TEST_FILE)
im.load()
self.assertEqual(im.mode, "RGBA")
self.assertEqual(im.size, (128, 128))
self.assertEqual(im.format, "MIC")
# Adjust for the gamma of 2.2 encoded into the file
lut = ImagePalette.make_gamma_lut(1/2.2)
im = Image.merge('RGBA', [chan.point(lut) for chan in im.split()])
im2 = hopper("RGBA")
self.assert_image_similar(im, im2, 10)
Example #30
| Source File: test_color_lut.py From python3_ios with BSD 3-Clause "New" or "Revised" License | 5 votes |
|
def test_identities_4_channels(self):
g = Image.linear_gradient('L')
im = Image.merge('RGB', [g, g.transpose(Image.ROTATE_90),
g.transpose(Image.ROTATE_180)])
# Red channel copied to alpha
self.assert_image_equal(
Image.merge('RGBA', (im.split()*2)[:4]),
im._new(im.im.color_lut_3d('RGBA', Image.LINEAR,
*self.generate_identity_table(4, 17))))
