def percentage_missing_data(df: 'DataFrame or Series', in_percentage: 'bool'=True, draw_graph: 'bool'=False):
"""
Return missing data per column (in percentage, if True)
input is a pandas dataframe or series
output is the number of missing rows (in percentage, if specified)
if draw_graph is false and in_percentage is false, return missing_data
if draw_graph is false and in_percentage is true, return missing_data_perc
if draw_graph is true and in_percentage is false, plot graph and return missing_data
if draw_graph is true and in_percentage is false, plot graph and return missing_data_perc"""
missing_data = df.isna().sum()[df.isna().sum() > 0].sort_values(ascending=False)
missing_data_perc = np.round(missing_data/df.shape[0] * 100, 2)
if not draw_graph and not in_percentage: # do not plot graph and output number of missing rows
print(f'Missing rows found in: {tuple(missing_data.index)}')
return missing_data
if not draw_graph and in_percentage: # don't plot graph and output percent of missing rows
print(f'Percentage number of missing rows for: {tuple(missing_data.index)}')
return missing_data_perc
# plot graph to display info
sns.set_theme(style='darkgrid')
fig = plt.figure(figsize=(6, 3), dpi=150)
ax = fig.add_axes(rect=[0, 0, 1, 1])
row_lab = "Missing Rows"
titl = "Missing Rows per Column"
if not in_percentage:
sns.barplot(y=missing_data.index, x=missing_data, ax=ax)
else:
row_lab = f"{row_lab} (in %)"
titl = f"{titl} (in %)"
sns.barplot(y=missing_data_perc.index, x=missing_data_perc, ax=ax)
ax.set_ylabel("Feature"), ax.set_xlabel(row_lab)
ax.set_title(titl)
# save graph as image
graph_folder = f'{os.getcwd()}\\DisplayGraphs'
joblib.os.makedirs(graph_folder, exist_ok=True) # folder created
graph_file = f'{graph_folder}\\plot1.png'
fig.savefig(fname=graph_file, pad_inches=0.25,
dpi=200, bbox_inches='tight')
# display saved figure image
from PIL import Image, ImageShow
img = Image.open(graph_file)
ImageShow.show(img)
if not in_percentage: # output number of missing rows
print('Number of missing rows:')
return missing_data
print('Percentage number of missing rows:')
return missing_data_perc # output percent of missing rows
def position(camera,actual_position,target_position,base,lnk1,lnk2):
print('Displaying camera.')
ImageShow.show(camera)
time = float(prompt('time ->'))
base = float(prompt('base ->', '%.1f' % base))
lnk1 = float(prompt('lnk1 ->', '%.1f' % lnk1))
lnk2 = float(prompt('lnk2 ->', '%.1f' % lnk2))
reset = False
return time, base, lnk1, lnk2, reset
def test_show(self):
class TestViewer:
methodCalled = False
def show(self, image, title=None, **options):
self.methodCalled = True
return True
viewer = TestViewer()
ImageShow.register(viewer, -1)
im = hopper()
self.assertTrue(ImageShow.show(im))
self.assertTrue(viewer.methodCalled)
def mesh(self, image):
width = 640
height = 480
pose_2d_mpiis = []
visibilities = []
# Re-samples the images and perform estimation
humans = self.args["estimator"].inference(image, resize_to_default=(
self.args["width"] > 0 and self.args["height"] > 0),
upsample_size=float(4))
# creates the body structure containing body points
structure = TfPoseEstimator.draw_humans(image, humans, imgcopy=False)
for human in humans:
pose_2d_mpii, visibility = common.MPIIPart.from_coco(human)
pose_2d_mpiis.append(
[(int(y * height + 0.5), int(x * width + 0.5)) for x, y in pose_2d_mpii]
)
# Contains the body points. If empty then body not found error encounter
visibilities.append(visibility)
# Generate 2D points
pose_2d_mpiis = np.array(pose_2d_mpiis)
visibilities = np.array(visibilities)
# Generate 3D points of 17 joints of body
transformed_pose2d, weights = self.args["pose"].transform_joints(pose_2d_mpiis, visibilities)
# pose_3d contains an matrix of size 17(body points)*3(x,y,z)
pose_3d = self.args["pose"].compute_3d(transformed_pose2d, weights)
# Take Transpose of the matrix and return a matrix of size 3*17
keypoints = pose_3d[0].transpose()
# chaning the color scheme of the image from RGB to BGR
output=Image.fromarray(cv.cvtColor(structure, cv.COLOR_RGB2BGR))
# Displaying Image on the frontend
ImageShow.show(output,title=self.url)
# window_name = "image " + str(self.window_counter)
# structure=ResizeWithAspectRatio(image=structure,height=786)
#
# cv.imshow(window_name, structure)
# cv.waitKey(10)
# thread = myThread(self.window_counter, name=window_name)
# thread.start()
# _thread.start_new_thread(create_window(),window_name)
# keypoints = keypoints
"""
return 3d keypoints
"""
return keypoints[13]
def test_show(self):
class TestViewer:
methodCalled = False
def show(self, image, title=None, **options):
self.methodCalled = True
return True
viewer = TestViewer()
ImageShow.register(viewer, -1)
im = hopper()
self.assertTrue(ImageShow.show(im))
self.assertTrue(viewer.methodCalled)
def test_showxv_deprecation(self):
class TestViewer(ImageShow.Viewer):
def show_image(self, image, **options):
return True
viewer = TestViewer()
ImageShow.register(viewer, -1)
im = Image.new("RGB", (50, 50), "white")
with pytest.warns(DeprecationWarning):
Image._showxv(im)
# Restore original state
ImageShow._viewers.pop(0)
def it_can_show_its_thumbnail(self, tmpdir):
slide, _ = base_test_slide(tmpdir,
PILIMG.RGBA_COLOR_500X500_155_249_240)
slide.save_thumbnail()
assert ImageShow.show(PIL.Image.open(slide.thumbnail_path))
def test_viewer(self):
viewer = ImageShow.Viewer()
self.assertIsNone(viewer.get_format(None))
self.assertRaises(NotImplementedError,
lambda: viewer.get_command(None))
def test_viewer():
viewer = ImageShow.Viewer()
assert viewer.get_format(None) is None
with pytest.raises(NotImplementedError):
viewer.get_command(None)
def test_show(self):
class TestViewer(ImageShow.Viewer):
methodCalled = False
def show_image(self, image, **options):
self.methodCalled = True
return True
viewer = TestViewer()
ImageShow.register(viewer, -1)
for mode in ("1", "I;16", "LA", "RGB", "RGBA"):
im = hopper(mode)
self.assertTrue(ImageShow.show(im))
self.assertTrue(viewer.methodCalled)
# Restore original state
ImageShow._viewers.pop(0)
def test_show_without_viewers():
viewers = ImageShow._viewers
ImageShow._viewers = []
im = hopper()
assert not ImageShow.show(im)
ImageShow._viewers = viewers
def test_viewer_show(order):
class TestViewer(ImageShow.Viewer):
def show_image(self, image, **options):
self.methodCalled = True
return True
viewer = TestViewer()
ImageShow.register(viewer, order)
for mode in ("1", "I;16", "LA", "RGB", "RGBA"):
viewer.methodCalled = False
with hopper(mode) as im:
assert ImageShow.show(im)
assert viewer.methodCalled
# Restore original state
ImageShow._viewers.pop(0)
def DrawText(text, bgImage):
image = Image.new('RGBA', (3 * 24, 24), color=(0, 0, 0, 0))
draw = ImageDraw.Draw(image)
font = ImageFont.truetype('C:/Windows/Fonts/simhei.ttf',
int(24.0 * 3.0 / len(text)),
encoding="unic")
draw.text((0, 0), text, (0, 0, 0, 160), font)
ImageShow.show(image)
image = image.rotate(random.uniform(-5, 5),
resample=Image.BICUBIC,
expand=1)
scaleWidth = int(bgImage.height / image.height * image.width)
image = image.resize((scaleWidth, bgImage.height), resample=Image.BICUBIC)
bgImageCrop = bgImage.crop(box=(0, 0, scaleWidth, bgImage.height))
image = Image.alpha_composite(bgImageCrop, image)
ImageShow.show(image)
return image.convert(mode='RGB')
def it_can_show_its_thumbnail(self, tmpdir):
tmp_path_ = tmpdir.mkdir("myslide")
image = PILIMG.RGBA_COLOR_500X500_155_249_240
image.save(os.path.join(tmp_path_, "mywsi.png"), "PNG")
slide_path = os.path.join(tmp_path_, "mywsi.png")
slide = Slide(slide_path, "processed")
slide.save_thumbnail()
assert ImageShow.show(PIL.Image.open(slide.thumbnail_path))
def handle_image_PIL(self, data, mime):
if mime not in ('image/png', 'image/jpeg'):
return False
try:
from PIL import Image, ImageShow
except ImportError:
return False
raw = base64.decodestring(data[mime].encode('ascii'))
img = Image.open(BytesIO(raw))
return ImageShow.show(img)
def handle_image_PIL(self, data, mime):
if mime not in ('image/png', 'image/jpeg'):
return False
try:
from PIL import Image, ImageShow
except ImportError:
return False
raw = base64.decodestring(data[mime].encode('ascii'))
img = Image.open(BytesIO(raw))
return ImageShow.show(img)
from PIL import ImageShow
import os
from src.denoiser.mean_pixel import MeanPixel
from src.denoiser.median_pixel import MedianPixel
from src.denoiser.cnn import CnnAutoencoder
import numpy as np
from PIL import ImageFilter
class FehViewer(ImageShow.UnixViewer):
def show_file(self, filename, **options):
os.system('feh %s' % filename)
return 1
ImageShow.register(FehViewer, order=-1)
def load_image(filename):
img = Image.open(filename)
img.load()
data = np.asarray(img, dtype=np.uint8)
return data.flatten()
def show_image_numpy(im):
im = Image.fromarray(im.reshape(480, 720, 3))
im.save("1.png")
im.show()
def showImage(self):
from PIL import Image, ImageShow
with Image.open(
r"C:\Users\cryos\Documents\Screenshot 2020-12-04 195747.jpg"
) as imag:
ImageShow.show(imag)
def test_register(self):
# Test registering a viewer that is not a class
ImageShow.register("not a class")
def test_show():
for mode in ("1", "I;16", "LA", "RGB", "RGBA"):
im = hopper(mode)
assert ImageShow.show(im)
import pydirectinput as pdi import pyautogui import time from getBoundingBox import getBoundingBox import cv2 import numpy from PIL import Image, ImageShow #first get the bounding box topLeft = getBoundingBox() img = pyautogui.screenshot(region=(topLeft[0], topLeft[1], 640, 400)) processedImage = numpy.asarray(img) print(processedImage.ndim) print(processedImage.shape) print(processedImage.size) print(processedImage[0, 0, :]) #PIL.ImageShow.show(img) newIm = Image.fromarray(processedImage) ImageShow.show(newIm)
def create_words_data_5on5_with_spaces(rel_in_path, rel_out_path, map_size,
format, images_num):
dir_in = './' + rel_in_path
dir_out = './' + rel_out_path
output_format = format
os.makedirs(dir_out, exist_ok=True)
env = lmdb.open(dir_out, map_size=map_size)
cache = {}
cnt = 1
dir_in_path = pathlib.Path(dir_in)
chr_dirs = os.listdir(dir_in_path)
idx_to_chr_path = defaultdict(def_value)
aleph = ord('א')
for chr_dir in chr_dirs:
# print(chr(int(chr_dir) + aleph))
chr_dir_path = dir_in + chr_dir
cur_chr_path = pathlib.Path(chr_dir_path)
chr_files = os.listdir(cur_chr_path)
for chr_file in chr_files:
cur_chr_img_path = chr_dir_path + '/' + chr_file
idx_to_chr_path[int(chr_dir)].append(cur_chr_img_path)
non_ending_letters = 'אבגדהוזחטיכלמנסעפצקרשת'
ending_letters = 'אבגדהוזחטיךלמןסעףץקרשת'
low_letters = 'נקךןת'
bg = './bg.jpg'
bg = Image.open(bg)
bg = np.asarray(bg)
words_count = 0
total_copies = []
total_bytes = 0
images_count = 0
while images_count < images_num:
one_or_two = np.random.randint(0, 10)
if one_or_two == 3:
word_len = np.random.randint(11, 20)
else:
word_len = np.random.randint(1, 11)
is_lower = np.zeros(word_len)
images = []
length_upper = 0
length_lower = 0
width = 0
label = ''
# letters generations separetly
for i in range(word_len - 1):
letter = np.random.randint(22)
if non_ending_letters[letter] in low_letters:
is_lower[word_len - 1 - i] = 1
letter_idx = ord(non_ending_letters[letter]) - ord('א')
label += chr(letter_idx + ord('א'))
letter_imgs = idx_to_chr_path[letter_idx]
amount = len(letter_imgs)
img_num = np.random.randint(amount - 1)
letter_img_path = letter_imgs[img_num]
cur_chr_img = Image.open(letter_img_path)
cur_chr_img = np.asarray(cur_chr_img)
cur_length, cur_width, channels = cur_chr_img.shape
if channels == 4: # remove the alpha channel
cur_chr_img = cur_chr_img[:, :, :-1]
width += cur_width
images.append(cur_chr_img)
if non_ending_letters[letter] in low_letters:
length_lower = max(length_lower, cur_length)
else:
length_upper = max(length_upper, cur_length)
# last letter in ending letters
letter = np.random.randint(22)
if ending_letters[letter] in low_letters:
is_lower[0] = 1
letter_idx = ord(ending_letters[letter]) - ord('א')
label += chr(letter_idx + ord('א'))
letter_imgs = idx_to_chr_path[letter_idx]
amount = len(letter_imgs)
img_num = np.random.randint(amount - 1)
letter_img_path = letter_imgs[img_num]
cur_chr_img = Image.open(letter_img_path)
cur_chr_img = np.asarray(cur_chr_img)
cur_length, cur_width, channels = cur_chr_img.shape
if channels == 4: # remove the alpha channel
cur_chr_img = cur_chr_img[:, :, :-1]
width += cur_width
images.append(cur_chr_img)
if non_ending_letters[letter] in low_letters:
length_lower = max(length_lower, cur_length)
else:
length_upper = max(length_upper, cur_length)
if length_upper > length_lower:
total_length = ceil(length_upper + length_lower / 2)
else:
total_length = ceil(length_lower + length_upper / 2)
# word generation from letters
# print(label)
# background_img = Image.fromarray(background)
# ImageShow.show(background_img)
# print()
# save image in lmdb
# _, format = chr_file.split('.')
# if output_format == 'same':
# output_format = format
# word writing to lmdb in compressed form with bytesIO - reduces total size
words_count += 1
# place diversity images generation
row_shift = 3
col_shift = 3
_, width_step, _ = list(reversed(images))[0].shape
copies = 0
for cls in range(col_shift + 1):
for rws in range(row_shift + 1):
for c in range(0, cls + 1):
for r in range(0, rws + 1):
width_start_idx = 0
background = np.copy(bg[0:total_length,
0:width * 2, :])
for i, (letter_img, is_low) in enumerate(
zip(reversed(images), is_lower)):
cur_len, cur_width, _ = letter_img.shape
if not is_low:
start_idx = length_upper - cur_len
else:
start_idx = total_length - cur_len
col_end_idx = width_start_idx + cur_width
background[start_idx:(start_idx + cur_len),
width_start_idx:(
col_end_idx), :] = letter_img
cur_space_width = cur_width / 10
cur_space = int(
np.random.randint(-2, 4) * cur_space_width)
if i < word_len - 1:
width_start_idx += cur_width + cur_space
else:
width_start_idx += cur_width
background = background[:,
0:width_start_idx, :]
cur_word_img = background
word_l, word_w, _ = background.shape
background = np.copy(
bg[0:word_l + word_l * cls,
0:word_w + width_step * rws, :])
background[c * word_l:(c + 1) * word_l,
r * width_step:word_w +
r * width_step, :] = cur_word_img
background_img = Image.fromarray(background)
ImageShow.show(background_img)
copies += 1
imageKey = 'image-%09d'.encode() % cnt
labelKey = 'label-%09d'.encode() % cnt
total_bytes += len(imageKey) + len(labelKey)
background = Image.fromarray(background)
with io.BytesIO() as output:
background.save(output, format=output_format)
imageBin = output.getvalue()
total_bytes += len(imageBin) + len(label.encode())
cache[imageKey] = imageBin
cache[labelKey] = label.encode()
if cnt % 1000 == 0:
env.set_mapsize(int(total_bytes * 1.12))
writeCache(env, cache)
cache = {}
print('Written %d' % cnt)
cnt += 1
images_count += copies
total_copies.append(copies)
if len(cache) != 0:
env.set_mapsize(int(total_bytes * 1.09))
writeCache(env, cache)
cache = {}
print('Written %d' % (cnt - 1))
nSamples = cnt - 1
cache['num-samples'.encode()] = str(nSamples).encode()
writeCache(env, cache)
print(
'Created dataset with %d samples of size %d bytes with %d words and %d copies in average'
%
(nSamples, total_bytes, words_count, np.asarray(total_copies).mean()))
def test_show(self):
for mode in ("1", "I;16", "LA", "RGB", "RGBA"):
im = hopper(mode)
self.assertTrue(ImageShow.show(im))
__all__.append('serial')
except ModuleNotFoundError as e:
pass
# try:
# # from .video import camera
# from . import display, rpycs
# __all__.extend(['display', 'video', 'rpycs', 'camera'])
# except ModuleNotFoundError as e:
# pass
try:
from . import nn
__all__.extend(['nn'])
except ModuleNotFoundError as e:
pass
try:
import shutil
from PIL import ImageShow
# use fbviewer on linux
# os.system('ln -s /usr/sbin/fbviewer /usr/sbin/display')
if shutil.which("fbviewer"):
class fbViewer(ImageShow.UnixViewer):
def get_command_ex(self, file, **options):
command = executable = "fbviewer"
return command, executable
ImageShow.register(fbViewer, 0)
except ModuleNotFoundError as e:
pass
class MyPrompts(Prompts):
def in_prompt_tokens(self, cli=None):
return [
(Token.Other, ">>> "),
]
def out_prompt_tokens(self):
return [
(Token.Prompt, ""),
]
class MyViewer(ImageShow.Viewer):
format = "png"
def get_command(self, file, **options):
w = 1920 // 2
h = w * 3 // 4
left = (1920 - w) // 2
top = (1080 - h) // 2
return rf'mpv --no-terminal --geometry={w}x{h}+{left}+{top} "{file}"'
ImageShow.register(MyViewer, order=-1)
ip = get_ipython()
ip.prompts = MyPrompts(ip)
os.system("cls")
def test_register(self):
# Test registering a viewer that is not a class
ImageShow.register("not a class")
def _showxv(image, title=None, **options):
from PIL import ImageShow
ImageShow.show(image, title, **options)
def test_register(self):
# Test registering a viewer that is not a class
ImageShow.register("not a class")
# Restore original state
ImageShow._viewers.pop()
def it_can_show_its_thumbnail(self, tmpdir):
slide, _ = base_test_slide(tmpdir,
PILIMG.RGBA_COLOR_500X500_155_249_240)
assert ImageShow.show(slide.thumbnail)
def test_register(self):
# Test registering a viewer that is not a class
ImageShow.register("not a class")
# Restore original state
ImageShow._viewers.pop()
def addDataToTable(table, headers, data):
table.setRowCount(0)
table.setColumnCount(0)
for i in range(len(headers)):
table.insertColumn(i)
table.setHorizontalHeaderLabels(headers)
j = 0
for row in data:
table.insertRow(j)
i = 0
for x in row:
table.setItem(j, i, QTableWidgetItem(x))
i += 1
j += 1
if __name__ == "__main__":
from PIL import ImageShow
data = {
"First Name": "Monish",
"Last Name": "Sudhagar",
"Gender": "Male",
"Date of Joining": "2020/11/01",
"Role": "Librarian"
}
ID = createQrId("c3f9d130-8524-4699-9b40-4e0f7d5bd4f5", data)
ImageShow.show(ID)
def Display(self):
return ImageShow.show(self.picture)
from PIL import ImageShow, Image
import pandas as pd
print("截止到2020/02/20 软件测试无误，由于学校登录系统有个登录状态码是加密的，所以可能随时失败，软件不兼容的联系班里最帅的那个帮忙导吧。。\n我已人品担保不会上传你的账号密码\n", "_"*30)
username = int(input("学号："))
password = str(input("密码："))
image_url = "http://jwgls.jmu.edu.cn/Common/CheckCode.aspx"
headers = {"User-Agent" : "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/80.0.3987.100 Safari/537.36 Edg/80.0.361.53"}
s = requests.Session()
response = s.get(image_url, headers=headers)
with open(r"check.jpg", "wb") as f:
f.write(response.content)
try:
check_image = Image.open(r"check.jpg")
ImageShow.show(check_image, title="验证码")
except:
print("抱歉显示验证码失败，请直接退出")
code = input("验证码：")
# plt.show()
data = {
"__VIEWSTATE":"/wEPDwUKMTA4MDEzMTMyOQ9kFgICAw9kFgICDw8PFgIeBFRleHQFATBkZBgBBR5fX0NvbnRyb2xzUmVxdWlyZVBvc3RCYWNrS2V5X18WAgUNQnRuTG9naW5JbWFnZQUNQnRuUmVzZXRJbWFnZcH71Q3NhGesjfuvAIN4VJIH4TsM",
"TxtUserName": username,
"TxtPassword": password,
"TxtVerifCode": int(code),
"BtnLoginImage.x":33,
"BtnLoginImage.y":7
}
login_url = "http://jwgls.jmu.edu.cn/login.aspx"
# print(data)
response = s.post(login_url, headers=headers, data=data)