def user_color(original, new):
'''There are two parameters. Original is the original image that has yet to
be modified. New is the image after it has been modified. First the image is
opened, and then there is raw input so that the user can input what color of
the border that they want and the size of the border. There is a try and
except structure used to by pass error so that the program still works even
though you enter an invalid value. The image with the customized border is
returned'''
img = Image.open(original) #opens original image
#adds border to original
color = raw_input('What color would you like the border to be?(Prompt \
will appear until all images have a chosen color.): \n')
thickness = raw_input(
'What width(in pixels) would you like the border to be? \
Please type an INTEGER!(Prompt will appear until all images are have a chosen\
width.): \n')
try:
img_with_border = ImageOps.expand(img,
border=int(thickness),
fill=str(color))
except ValueError:
img_with_border = ImageOps.expand(img,
border=int(30),
fill=str("blue"))
return img_with_border
def processOneImage(imageFile, imageLabel):
image = Image.open(imageFile, "rb");
buffer = np.array(image);
IMAGE_WIDTH = string.atoi(G_OPTION.getValue("width"));
IMAGE_HEIGHT = string.atoi(G_OPTION.getValue("height"));
IMAGE_CHANNEL = string.atoi(G_OPTION.getValue("channel"));
buffer = buffer.reshape([IMAGE_WIDTH, IMAGE_HEIGHT, IMAGE_CHANNEL])
mode = G_OPTION.getValue("mode")
for char in mode:
if(char == 'm'):
#substract
buffer=subtractmean(buffer)
return
else:
#normalize
if(char == 'n'):
return
else:
#whitening
if(char == "w"):
return
else:
if(char == "c"):
return
def update(self):
if isinstance(self.line,matplotlib.image.AxesImage):
# image name
try:
if len(self.xdata)==0 and self.dataName: self.xdata=self.imgData[self.dataName] # empty list reference an empty singleton, not the list we want; adjust here
import Image
if self.xdata[current]==None: img=Image.new('RGBA',(1,1),(0,0,0,0))
else: img=Image.open(self.xdata[current])
self.line.set_data(img)
except IndexError: pass
else:
# regular data
import numpy
# current==-1 avoids copy slicing data in the else part
if current==None or current==-1 or afterCurrentAlpha==1:
self.line.set_xdata(self.xdata); self.line.set_ydata(self.ydata)
self.line2.set_xdata([]); self.line2.set_ydata([])
else:
try: # try if we can extend the first part by one so that lines are connected
self.xdata[:current+1]; preCurrEnd=current+1
except IndexError: preCurrEnd=current
preCurrEnd=current+(1 if len(self.xdata)>current else 0)
self.line.set_xdata(self.xdata[:preCurrEnd]); self.line.set_ydata(self.ydata[:preCurrEnd])
self.line2.set_xdata(self.xdata[current:]); self.line2.set_ydata(self.ydata[current:])
try:
x,y=self.xdata[current],self.ydata[current]
except IndexError: x,y=0,0
# this could be written in a nicer way, very likely
try:
pt=numpy.ndarray((2,),buffer=numpy.array([float(x),float(y)]))
if self.scatter:
self.scatter.set_offsets(pt)
# change rotation of the marker (possibly incorrect)
try:
dx,dy=self.xdata[current]-self.xdata[current-1],self.ydata[current]-self.ydata[current-1]
# smoothing from last n values, if possible
# FIXME: does not show arrow at all if less than window values
#try:
# window=10
# dx,dy=[numpy.average(numpy.diff(dta[current-window:current])) for dta in self.xdata,self.ydata]
#except IndexError: pass
# there must be an easier way to find on-screen derivative angle, ask on the matplotlib mailing list
axes=self.line.get_axes()
p=axes.patch; xx,yy=p.get_verts()[:,0],p.get_verts()[:,1]; size=max(xx)-min(xx),max(yy)-min(yy)
aspect=(size[1]/size[0])*(1./axes.get_data_ratio())
angle=math.atan(aspect*dy/dx)
if dx<0: angle-=math.pi
self.scatter.set_transform(matplotlib.transforms.Affine2D().rotate(angle))
except IndexError: pass
if self.annotation:
if math.isnan(x) or math.isnan(y):
if hasattr(self.annotation,'xyann'): self.annotation.xyann=(x,y)
else: self.annotation.xytext=(0,0)
self.annotation.set_text('') # make invisible, place anywhere
else:
#
if hasattr(self.annotation,'xyann'): self.annotation.xyann=(x,y) # newer MPL versions (>=1.4)
else: self.annotation.xyann=(x,y)
self.annotation.set_text(self.annotation.annotateFmt.format(xy=(float(x),float(y))))
except TypeError: pass # this happens at i386 with empty data, saying TypeError: buffer is too small for requested array
def gray_scale(original, new):
'''There are two parameters. Original is the original image that has yet to
be modified. New is the image after it has been modified. First, we open the
images that aren't modified yet, and then, we open the logo. We use imageOps
to change the image into grayscale and then we paste the logo onto the
image. We don't set the logo equal to the mask because we want the logo to
have a black background. After the logo is pasted, we return the image with
the pasted logo and grayscale'''
image_file = Image.open(original) # open colour image
img = Image.open('ourlogo.png')
grayscale = ImageOps.grayscale(image_file)
width, height = grayscale.size
logo_small = img.resize((78, 86))
grayscale.paste(logo_small, (width - 90, 5))
return grayscale
def ExtractData(Nom): # Renvoie un tableau H*L*3
im = Image.open(Nom) # Lecture de l’image
L, H = im.size # Taille de l’image
data = im.getdata() # On récupère les données dans la variable data
d = np.array(data) # conversion de data en tableau
IMA = d.reshape(
(H, L, 3)) # On transforme un tableau 1D en tableau avec 3 indices.
return IMA # Renvoie un tableau de dimension H*L*3
def __getitem__(self, item):
sample = {
'image':
self.transform(Image.open(self.images[item]).convert('RGB'))
}
if self.labels is not None:
sample['label'] = self.labels[item]
sample['attributes'] = self.attributes[sample['label']]
sample['word_embeddings'] = self.word_embeddings[sample['label']]
return sample
def load_test(path):
resize_trans=transforms.Compose([transforms.Resize(size=(60,60)),transforms.ToTensor()])
if not os.path.exists(path):
print('File {} doesnt exist'.format(path))
else:
img = Image.open(path)
img = img.convert(mode='L')
img = resize_trans(img)
x = img.view(1,1,60,60)
return(img.view(60,60).numpy(),x)
def process_image(image):
img_transforms = transforms.Compose([
transforms.Resize(255),
transforms.CenterCrop(224),
transforms.ToTensor(),
transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])
])
img = img_transforms(Image.open(image))
return img
def run(self):
figwidth = self.options.pop('figwidth', None)
figclasses = self.options.pop('figclass', ["right"])
align = self.options.pop('align', None)
(media_node, ) = Media.run(self)
if isinstance(media_node, nodes.system_message):
return [media_node]
figure_node = nodes.figure('', media_node)
if figwidth == 'image':
if PIL and self.state.document.settings.file_insertion_enabled:
# PIL doesn't like Unicode paths:
try:
i = PIL.open(str(media_node['uri']))
except (IOError, UnicodeError):
pass
else:
self.state.document.settings.record_dependencies.add(
media_node['uri'])
figure_node['width'] = i.size[0]
elif figwidth is not None:
figure_node['width'] = figwidth
if figclasses:
figure_node['classes'] += figclasses
if align:
figure_node['align'] = align
if self.content:
node = nodes.Element() # anonymous container for parsing
self.state.nested_parse(self.content, self.content_offset, node)
first_node = node[0]
if isinstance(first_node, nodes.paragraph):
caption = nodes.caption(first_node.rawsource, '',
*first_node.children)
figure_node += caption
elif not (isinstance(first_node, nodes.comment)
and len(first_node) == 0):
error = self.state_machine.reporter.error(
'Figure caption must be a paragraph or empty comment.',
nodes.literal_block(self.block_text, self.block_text),
line=self.lineno)
return [figure_node, error]
if len(node) > 1:
figure_node += nodes.legend('', *node[1:])
node = figure_node
node['label'] = self.options.get('label', None)
if not node['label']:
node['label'] = self.options.get('uri')
node['number'] = None
ret = [node]
if node['label']:
key = node['label']
tnode = nodes.target('', '', ids=['figure-' + node['label']])
self.state.document.note_explicit_target(tnode)
ret.insert(0, tnode)
return ret
def multi_border(originalimg, new):
''' Module for adding borders to images in folders '''
img = Image.open(originalimg) #opens original image
#adds border to original
img_with_border1 = ImageOps.expand(img, border=30, fill='blue')
img_with_border2 = ImageOps.expand(img_with_border1,
border=30,
fill='white')
img_with_border3 = ImageOps.expand(img_with_border2, border=30, fill='red')
return img_with_border3
def imgSizeChanger(size, file_name, new_file_name):
new_img = Image.new("RGB", size, "white")
im = Image.open(file_name)
im.thumbnail(size, Image.ANTIALIAS)
load_img = im.load()
load_newimg = new_img.load()
i_offset = (size - im.size[0]) / 2
j_offset = (size - im.size[1]) / 2
for i in range(0, im.size[0]):
for j in range(0, im.size[1]):
load_newimg[i + i_offset, j + j_offset] = load_img[i, j]
new_img.save(new_file_name, "JPEG")
def multi_border(original, new):
'''There are two parameters. Original is the original image that has yet to
be modified. New is the image after it has been modified. First, the
function upens the image, and then wit ImageOps, three borders are made by
adding a border around the image three times. One is red, one is blue and
one is white. Then, the logo image is opened and it is pasted onto the image
with three borders after it is resized to a smaller scale. The mask is set
to the logo because if it isn't, the png would have a black background'''
img = Image.open(original) #opens original image
#adds border to original
img_with_border1 = ImageOps.expand(img, border=30, fill='blue')
img_with_border2 = ImageOps.expand(img_with_border1,
border=30,
fill='white')
img_with_border3 = ImageOps.expand(img_with_border2, border=30, fill='red')
width, height = img_with_border3.size
img = Image.open('ourlogo.png')
logo_small = img.resize((78, 86))
img_with_border3.paste(logo_small, (width - 190, 90), mask=logo_small)
return img_with_border3
def distorted_colored(original, new):
'''There are two parameters. Original is the original image that has yet to
be modified. New is the image after it has been modified. First the image is
opened, and then, with ImageOps, and assigning variables specific colors, we
are able to colorize the image into a red and blue image that makes it have
some wierd and distorted colors. The red and blue colored image is
returned'''
image_file = Image.open(original) # open colour image
grayscale = ImageOps.grayscale(image_file)
BLUE = "#0000FF"
RED = "#FF0000"
distorted_pic = ImageOps.colorize(grayscale, RED, BLUE)
return distorted_pic
def calculate(self, imgs): try: img1 = Image.open(str(imgs[0])) img2 = Image.open(str(imgs[1])) if img1.size != img2.size or img1.getbands() != img2.getbands(): return -1 s = 0 for band_index, band in enumerate(img1.getbands()): m1 = np.array([p[band_index] for p in img1.getdata()]).reshape(*img1.size) m2 = np.array([p[band_index] for p in img2.getdata()]).reshape(*img2.size) s += np.sum(np.abs(m1-m2)) s = s/1000000 (filepath1, filename1) = os.path.split(str(imgs[0])) (filepath2, filename2) = os.path.split(str(imgs[1])) label = filename1 + "-" + filename2 return (label, s) except Exception, e: QMessageBox.warning(self, "Messaggio", str(e), QMessageBox.Ok)
def calculate(self, imgs):
try:
img1 = Image.open(str(imgs[0]))
img2 = Image.open(str(imgs[1]))
if img1.size != img2.size or img1.getbands() != img2.getbands():
return -1
s = 0
for band_index, band in enumerate(img1.getbands()):
m1 = np.array([p[band_index]
for p in img1.getdata()]).reshape(*img1.size)
m2 = np.array([p[band_index]
for p in img2.getdata()]).reshape(*img2.size)
s += np.sum(np.abs(m1 - m2))
s = s / 1000000
(filepath1, filename1) = os.path.split(str(imgs[0]))
(filepath2, filename2) = os.path.split(str(imgs[1]))
label = filename1 + "-" + filename2
return (label, s)
except Exception as e:
QMessageBox.warning(self, "Messaggio", str(e), QMessageBox.Ok)
def border_one(original_image, percent_of_side=.3):
"""There are two parameters, original_image represents the image before it
is modified, and percent_of_side is set to .3. There is a border that is
made with masks that are transparent so that you can see the brown canvas
behind the image. Our logo of the image is then pasted onto the bordered
image, and then it is returned"""
#set the radius of the rounded corners
width, height = original_image.size
###
#create a mask
###
#start with transparent mask
border_mask = PIL.Image.new('RGBA', (width, height), (127, 0, 127, 0))
drawing_layer = PIL.ImageDraw.Draw(border_mask)
# Overwrite the RGBA values with A=255.
# The 127 for RGB values was used merely for visualizing the mask
# Draw two rectangles to fill interior with opaqueness
drawing_layer.polygon([(0, 0), (width, 0), (width, height), (0, height)],
fill=(127, 0, 127, 150))
drawing_layer.polygon([(0, 0), (30, 0), (30, height), (0, height)],
fill=(0, 0, 255, 0),
outline=(0, 255, 0, 1))
drawing_layer.polygon([(width, 0), (width - 30, 0), (width - 30, height),
(width, height)],
fill=(0, 0, 255, 0),
outline=(0, 255, 0, 1))
drawing_layer.polygon([(0, 0), (width, 0), (width, 30), (0, 30)],
fill=(0, 0, 255, 0),
outline=(0, 255, 0, 1))
drawing_layer.polygon([(0, height), (width, height), (width, height - 30),
(0, height - 30)],
fill=(0, 0, 255, 0),
outline=(0, 255, 0, 1))
# Make the new image, starting with all transparent
result = PIL.Image.new('RGBA', original_image.size, (136, 39, 16, 255))
result.paste(original_image, (0, 0), mask=border_mask)
img = Image.open('ourlogo.png')
logo_small = img.resize((85, 93))
result.paste(logo_small, (width - 130, 40), mask=logo_small)
return result
def _get_border_image(self, type_):
if type_ not in self.Borders:
raise ValueError(
'Unknown border "{}". Available types: {}'.format(
type_, ', '.join(self.list_border_types())))
border_dir = os.path.join(os.path.dirname(__file__), 'data',
'borders')
match_file = self.Borders[type_]
for fname in glob.glob(os.path.join(border_dir, 'border*')):
if fname == match_file:
img = PIL.open(fname)
break
else:
raise RuntimeError(
'Border image "{}" not found in dir "{}"'.format(
match_file, border_dir))
return img
def generateMaps(mapFileName, numMaps, start_state, goal_state):
# Inputs:
# mapFileName - string of the file name (including local path)
# numMaps - number of maps to be generated
#
# Outputs:
# generatedMap_cell - cell array containing numMaps+1 maps
# the first element contains the seed map
#
import PIL
import matplotlib.plyplot as plt
map_seed = PIL.open(mapFileName).convert('L')
bridge_ind = numpy.where(map_seed != 0 & map_seed !=
1) # locations in the map where a bridge exists
bridge_probs = map_seed[bridge_ind] # probability for those bridges
N = bridge_ind.shape[0] # Number of bridges
# Holds the output for the generated bridges
generatedMap_cell = []
for i in range(0, numMaps):
temp_map = map_seed
rand_vals = np.rand(N, 1) # generate a random value for each bridge
bridge_vals = rand_vals < bridge_probs # are the bridges open?
temp_map[bridge_ind] = bridge_vals # create the maps
generatedMap_cell[i] = temp_map # store the maps in the cell array
#plot the maps for testing
plt.figure(i)
plt.imshow(scipy.misc.imresize(temp_map, 5, interp='nearest'))
(N, M) = map_seed.shape
(x, y) = numpy.meshgrid(numpy.arange(1, N + 1), numpy.arange(1, M + 1))
map_struct['map_name'] = mapFileName
map_struct['bridge_locations'] = np.array(
[x(bridge_ind).T, y(bridge_ind).T])
map_struct['bridge_probabilities'] = bridge_probs
map_struct['seed_map'] = map_seed
map_struct['map_samples'] = generatedMap_cell
map_struct['start'] = start_state
map_struct['goal'] = goal_state
def register(request):
# pass
if request.method == "POST":
user_name = request.POST.get('username', '')
pass_word_1 = request.POST.get('password_1', '')
pass_word_2 = request.POST.get('password_2', '')
nick_name = request.POST.get('nickname', '')
email = request.POST.get('email', '')
avatar = request.FILES.get('avatar')
if User.objects.filter(username=user_name):
return render(request, 'blog/register.html', {'error': '用户已存在'})
if (pass_word_1 != pass_word_2):
return render(request, 'blog/register.html', {'error': '两次密码输入不一致'})
user = User()
# 将头像设置为圆形
if avatar:
user.avatar = 'media/' + user_name + '.png'
img = Image.open(avatar)
size = img.size
r2 = min(size[0], size(1))
if size[0] != size[1]:
img = img.resize((r2, r2), Image.ANTIALIAS)
r3 = int(r2 / 2)
img_circle = Image.new('RGBA', (r3 * 2, r3 * 2), (255, 255, 255, 0))
pima = img.load()
pimb = img_circle.load()
r = float(r2 / 2)
for i in range(r2):
for j in range(r2):
lx = abs(i - r)
ly = abs(j - r)
l = (pow(lx, 2) + pow(ly, 2)) ** 0.5
if l < r3:
pimb[i - (r - r3), j - (r - r3)] = pima[i, j]
img_circle.save('static/media/' + user_name + '.png')
user.username = user_name
user.password = pass_word_1
user.email = email
user.nickname = nick_name
user.save()
return render(request, 'blog/index_unlogin.html')
else:
return render(request, 'blog/register.html')
def to_numpy(item):
'''
convert input to numpy array
input type: image-file-name, PIL image, torch tensor, numpy array
'''
if 'str' in str(type(item)): # read the image as numpy array
item = np.array(Image.open(item))
elif 'PIL' in str(type(item)):
item = np.array(item)
elif 'torch' in str(type(item)):
item = item.numpy()
elif 'imageio' in str(type(item)):
item = np.array(item)
elif 'numpy' in str(type(item)):
pass
else: # unsupported type
print('WTF:', str(type(item)))
return None
return item
def generateMaps(mapFileName, numMaps, start_state, goal_state):
# Inputs:
# mapFileName - string of the file name (including local path)
# numMaps - number of maps to be generated
#
# Outputs:
# generatedMap_cell - cell array containing numMaps+1 maps
# the first element contains the seed map
#
import PIL
import matplotlib.plyplot as plt
map_seed = PIL.open(mapFileName).convert('L')
bridge_ind = numpy.where(map_seed != 0 & map_seed != 1) # locations in the map where a bridge exists
bridge_probs = map_seed[bridge_ind] # probability for those bridges
N = bridge_ind.shape[0] # Number of bridges
# Holds the output for the generated bridges
generatedMap_cell = []
for i in range(0,numMaps):
temp_map = map_seed
rand_vals = np.rand(N,1) # generate a random value for each bridge
bridge_vals = rand_vals < bridge_probs # are the bridges open?
temp_map[bridge_ind] = bridge_vals # create the maps
generatedMap_cell[i] = temp_map # store the maps in the cell array
#plot the maps for testing
plt.figure(i)
plt.imshow(scipy.misc.imresize(temp_map,5, interp = 'nearest'))
(N, M) = map_seed.shape
(x, y) = numpy.meshgrid(numpy.arange(1,N+1), numpy.arange(1,M+1))
map_struct['map_name'] = mapFileName
map_struct['bridge_locations'] = np.array([x(bridge_ind).T, y(bridge_ind).T])
map_struct['bridge_probabilities'] = bridge_probs
map_struct['seed_map'] = map_seed
map_struct['map_samples'] = generatedMap_cell
map_struct['start'] = start_state
map_struct['goal'] = goal_state
def pdf2img(pdf_path):
image_list = []
try:
doc = fitz.open(pdf_path)
for page_index, page in enumerate(doc):
trans = fitz.Matrix(2.0, 2.0).preRotate(0)
pm = page.getPixmap(matrix=trans, alpha=False) # 获得每一页的流对象
getpngdata = pm.getImageData(output="png")
# 解码为 np.uint8
image_array = np.frombuffer(getpngdata, dtype=np.uint8)
img = cv2.imdecode(image_array, cv2.IMREAD_ANYCOLOR)
image_list.append(img)
except:
image_pdf = Image(filename=pdf_path, resolution=200)
with image_pdf.convert('jpg') as conv:
for img in conv.sequence:
img_page = Image(image=img).make_blob('jpg')
image = io.BytesIO(img_page)
img = np.array(PI.open(image).convert('RGB'))
image_list.append(img)
return image_list
def savePlotSequence(P,fileBase,stride=1,imgRatio=(5,7),title=None,titleFrames=20,lastFrames=30):
'''Save sequence of plots, each plot corresponding to one line in history. It is especially meant to be used for :obj:`woo.utils.makeVideo`.
:param stride: only consider every stride-th line of history (default creates one frame per each line)
:param title: Create title frame, where lines of title are separated with newlines (``\\n``) and optional subtitle is separated from title by double newline.
:param int titleFrames: Create this number of frames with title (by repeating its filename), determines how long the title will stand in the movie.
:param int lastFrames: Repeat the last frame this number of times, so that the movie does not end abruptly.
:return: List of filenames with consecutive frames.
'''
data,imgData,plots=P.data,P.imgData,P.plots
fig=createPlots(P,noShow=True,replace=True,subPlots=True,scatterSize=60,wider=True)[0]
sqrtFigs=math.sqrt(len(plots))
fig.set_size_inches(8*sqrtFigs,5*sqrtFigs) # better readable
fig.subplots_adjust(left=.05,right=.95,bottom=.05,top=.95) # make it more compact
if len(plots)==1 and plots[plots.keys()[0]]==None: # only pure snapshot is there
fig.set_size_inches(5,5)
fig.subplots_adjust(left=0,right=1,bottom=0,top=1)
#if not data.keys(): raise ValueError("plot.data is empty.")
pltLen=max(len(data[data.keys()[0]]) if data else 0,len(imgData[imgData.keys()[0]]) if imgData else 0)
if pltLen==0: raise ValueError("Both plot.data and plot.imgData are empty.")
global current
ret=[]
print 'Saving %d plot frames, it can take a while...'%(pltLen)
for i,n in enumerate(range(0,pltLen,stride)):
current=n
for l in P.currLineRefs: l.update()
out=fileBase+'-%03d.png'%i
fig.savefig(out)
ret.append(out)
sys.stderr.write('[%d]'%i)
if len(ret)==0: raise RuntimeError("No images created?!")
if title:
import Image
titleImgName=fileBase+'-title.png'
createTitleFrame(titleImgName,Image.open(ret[-1]).size,title)
ret=titleFrames*[titleImgName]+ret
if lastFrames>1: ret+=(lastFrames-1)*[ret[-1]]
return ret
def savePlotSequence(P,fileBase,stride=1,imgRatio=(5,7),title=None,titleFrames=20,lastFrames=30):
'''Save sequence of plots, each plot corresponding to one line in history. It is especially meant to be used for :obj:`woo.utils.makeVideo`.
:param stride: only consider every stride-th line of history (default creates one frame per each line)
:param title: Create title frame, where lines of title are separated with newlines (``\\n``) and optional subtitle is separated from title by double newline.
:param int titleFrames: Create this number of frames with title (by repeating its filename), determines how long the title will stand in the movie.
:param int lastFrames: Repeat the last frame this number of times, so that the movie does not end abruptly.
:return: List of filenames with consecutive frames.
'''
data,imgData,plots=P.data,P.imgData,P.plots
fig=createPlots(P,noShow=True,replace=True,subPlots=True,scatterSize=60,wider=True)[0]
sqrtFigs=math.sqrt(len(plots))
fig.set_size_inches(8*sqrtFigs,5*sqrtFigs) # better readable
fig.subplots_adjust(left=.05,right=.95,bottom=.05,top=.95) # make it more compact
if len(plots)==1 and plots[list(plots.keys())[0]]==None: # only pure snapshot is there
fig.set_size_inches(5,5)
fig.subplots_adjust(left=0,right=1,bottom=0,top=1)
#if not data.keys(): raise ValueError("plot.data is empty.")
pltLen=max(len(data[list(data.keys())[0]]) if data else 0,len(imgData[list(imgData.keys())[0]]) if imgData else 0)
if pltLen==0: raise ValueError("Both plot.data and plot.imgData are empty.")
global current
ret=[]
print('Saving %d plot frames, it can take a while...'%(pltLen))
for i,n in enumerate(range(0,pltLen,stride)):
current=n
for l in P.currLineRefs: l.update()
out=fileBase+'-%03d.png'%i
fig.savefig(out)
ret.append(out)
sys.stderr.write('[%d]'%i)
if len(ret)==0: raise RuntimeError("No images created?!")
if title:
import Image
titleImgName=fileBase+'-title.png'
createTitleFrame(titleImgName,Image.open(ret[-1]).size,title)
ret=titleFrames*[titleImgName]+ret
if lastFrames>1: ret+=(lastFrames-1)*[ret[-1]]
return ret
def user_color(original, new):
'''allows user to change border colors from set options'''
img = Image.open(original) #opens original image
#adds border to original
color = raw_input('What color would you like the border to be?(Prompt \
will appear until all images are have a chosen color.): \n')
time.sleep(1)
thic = raw_input('What width would you like the border to be?(Prompt \
will appear until all images are have a chosen width.): \n')
try:
img_with_border = ImageOps.expand(img,
border=int(thic),
fill=str(color))
except ValueError:
img_with_border = ImageOps.expand(img, border=30, fill=str("blue"))
try:
img_with_border = ImageOps.expand(img,
border=int(thic),
fill=str(color))
except TypeError:
img_with_border = ImageOps.expand(img, border=30, fill=str("blue"))
return img_with_border
def rescale(data, width, height, force=True):
"""Rescale the given image, optionally cropping it to make sure the result image has the specified width and height."""
max_width = width
max_height = height
input_file = StringIO(data)
img = pil.open(input_file)
if not force:
img.thumbnail((max_width, max_height), pil.ANTIALIAS)
else:
src_width, src_height = img.size
src_ratio = float(src_width) / float(src_height)
dst_width, dst_height = max_width, max_height
dst_ratio = float(dst_width) / float(dst_height)
if dst_ratio < src_ratio:
crop_height = src_height
crop_width = crop_height * dst_ratio
x_offset = float(src_width - crop_width) / 2
y_offset = 0
else:
crop_width = src_width
crop_height = crop_width / dst_ratio
x_offset = 0
y_offset = float(src_height - crop_height) / 3
img = img.crop((x_offset, y_offset, x_offset+int(crop_width), y_offset+int(crop_height)))
img = img.resize((dst_width, dst_height), pil.ANTIALIAS)
tmp = StringIO()
img.save(tmp, 'JPEG')
tmp.seek(0)
output_data = tmp.getvalue()
input_file.close()
tmp.close()
return output_data
import PIL as IMAGE file_src = 'img processing/imgs/fire/T0t0.jpg' #需要压缩的图片地址 img_src = 'img processing/imgs/fire/yasuo.jpg' #压缩后的图片地址 img = IMAGE.open(file_src) w, h = img.size w, h = round(w * 0.2), round(h * 0.2) # 去掉浮点，防报错 img = img.resize((w, h), IMAGE.ANTIALIAS) img.save(img_src, optimize=True, quality=85) # 质量为85效果最好
def border_one(original_image, percent_of_side=.3):
""" Rounds the corner of a PIL.Image
original_image must be a PIL.Image
Returns a new PIL.Image with rounded corners, where
0 < percent_of_side < 1 is the corner radius as a portion of the shorter
dimension of original_image
"""
#set the radius of the rounded corners
width, height = original_image.size
###
#create a mask
###
#start with transparent mask
border_mask = PIL.Image.new('RGBA', (width, height), (127, 0, 127, 0))
drawing_layer = PIL.ImageDraw.Draw(border_mask)
# Overwrite the RGBA values with A=255.
# The 127 for RGB values was used merely for visualizing the mask
# Draw two rectangles to fill interior with opaqueness
if width >= 300 or height >= 300:
drawing_layer.polygon([(0, 0), (width, 0), (width, height),
(0, height)],
fill=(127, 0, 127, 170))
drawing_layer.polygon([(0, 0), (30, 0), (30, height), (0, height)],
fill=(0, 0, 255, 0),
outline=(0, 255, 0, 1))
drawing_layer.polygon([(width, 0), (width - 30, 0),
(width - 30, height), (width, height)],
fill=(0, 0, 255, 0),
outline=(0, 255, 0, 1))
drawing_layer.polygon([(0, 0), (width, 0), (width, 30), (0, 30)],
fill=(0, 0, 255, 0),
outline=(0, 255, 0, 1))
drawing_layer.polygon([(0, height), (width, height),
(width, height - 30), (0, height - 30)],
fill=(0, 0, 255, 0),
outline=(0, 255, 0, 1))
# Make the new image, starting with all transparent
result = PIL.Image.new('RGBA', original_image.size, (136, 39, 16, 255))
result.paste(original_image, (0, 0), mask=border_mask)
img = Image.open('ourlogo_test.png')
logo_small = img.resize((85, 93))
result.paste(logo_small, (width - 130, 40), mask=logo_small)
return result
elif width <= 300 and height <= 300:
original_image.size = 500, 500
drawing_layer.polygon([(0, 0), (width, 0), (width, height),
(0, height)],
fill=(127, 0, 127, 170))
drawing_layer.polygon([(0, 0), (20, 0), (20, height), (0, height)],
fill=(0, 0, 255, 0),
outline=(0, 255, 0, 1))
drawing_layer.polygon([(width, 0), (width - 20, 0),
(width - 20, height), (width, height)],
fill=(0, 0, 255, 0),
outline=(0, 255, 0, 1))
drawing_layer.polygon([(0, 0), (width, 0), (width, 20), (0, 20)],
fill=(0, 0, 255, 0),
outline=(0, 255, 0, 1))
drawing_layer.polygon([(0, height), (width, height),
(width, height - 30), (0, height - 30)],
fill=(0, 0, 255, 0),
outline=(0, 255, 0, 1))
# Make the new image, starting with all transparent
result = PIL.Image.new('RGBA', original_image.size, (136, 39, 16, 255))
result.paste(original_image, (0, 0), mask=border_mask)
img = Image.open('ourlogo_test.png')
logo_small = img.resize((10, 23))
result.paste(logo_small, (width - 130, 40), mask=logo_small)
return result
def update(self):
if isinstance(self.line,matplotlib.image.AxesImage):
# image name
try:
if len(self.xdata)==0 and self.dataName: self.xdata=self.imgData[self.dataName] # empty list reference an empty singleton, not the list we want; adjust here
import Image
if self.xdata[current]==None: img=Image.new('RGBA',(1,1),(0,0,0,0))
else: img=Image.open(self.xdata[current])
self.line.set_data(img)
except IndexError: pass
else:
# regular data
import numpy
# current==-1 avoids copy slicing data in the else part
if current==None or current==-1 or afterCurrentAlpha==1:
self.line.set_xdata(self.xdata); self.line.set_ydata(self.ydata)
self.line2.set_xdata([]); self.line2.set_ydata([])
else:
try: # try if we can extend the first part by one so that lines are connected
self.xdata[:current+1]; preCurrEnd=current+1
except IndexError: preCurrEnd=current
preCurrEnd=current+(1 if len(self.xdata)>current else 0)
self.line.set_xdata(self.xdata[:preCurrEnd]); self.line.set_ydata(self.ydata[:preCurrEnd])
self.line2.set_xdata(self.xdata[current:]); self.line2.set_ydata(self.ydata[current:])
try:
x,y=self.xdata[current],self.ydata[current]
except IndexError: x,y=0,0
# this could be written in a nicer way, very likely
try:
pt=numpy.ndarray((2,),buffer=numpy.array([float(x),float(y)]))
if self.scatter:
self.scatter.set_offsets(pt)
# change rotation of the marker (possibly incorrect)
try:
dx,dy=self.xdata[current]-self.xdata[current-1],self.ydata[current]-self.ydata[current-1]
# smoothing from last n values, if possible
# FIXME: does not show arrow at all if less than window values
#try:
# window=10
# dx,dy=[numpy.average(numpy.diff(dta[current-window:current])) for dta in self.xdata,self.ydata]
#except IndexError: pass
# there must be an easier way to find on-screen derivative angle, ask on the matplotlib mailing list
# XXX: this can be siplified once we drop support for matplotlib < 1.5
# XXX: and is here to avoid MatplotlibDeprecationWarning for newer versions
axes=_my_get_axes(self.line)
p=axes.patch; xx,yy=p.get_verts()[:,0],p.get_verts()[:,1]; size=max(xx)-min(xx),max(yy)-min(yy)
aspect=(size[1]/size[0])*(1./axes.get_data_ratio())
if dx==0: angle=math.pi
angle=math.atan(aspect*dy/dx)
if dx<0: angle-=math.pi
self.scatter.set_transform(matplotlib.transforms.Affine2D().rotate(angle))
except IndexError: pass
if self.annotation:
if math.isnan(x) or math.isnan(y):
if hasattr(self.annotation,'xyann'): self.annotation.xyann=(x,y)
else: self.annotation.xytext=(0,0)
self.annotation.set_text('') # make invisible, place anywhere
else:
#
if hasattr(self.annotation,'xyann'): self.annotation.xyann=(x,y) # newer MPL versions (>=1.4)
else: self.annotation.xyann=(x,y)
self.annotation.set_text(self.annotation.annotateFmt.format(xy=(float(x),float(y))))
except TypeError: pass # this happens at i386 with empty data, saying TypeError: buffer is too small for requested array
def createPlots(P,subPlots=True,noShow=False,replace=True,scatterSize=60,wider=False):
'''Create plots based on current data;
:param subPlots: show all plots in one figure as subplots; otherwise, create multiple figures
:param noShow: use headless backend for plots, and do not show plots on the screen
:param replace: do not close existing figures, and do not update P.currLineRefs
'''
import logging
data,imgData,plots,labels,xylabels,legendLoc,axesWd,annotateFmt=P.data,P.imgData,P.plots,P.labels,P.xylabels,P.legendLoc,P.axesWd,P.annotateFmt
if replace:
if P.currLineRefs:
logging.info('Closing existing figures')
ff=set([_my_get_axes(l.line).get_figure() for l in P.currLineRefs]) # get all current figures
for f in ff: pylab.close(f) # close those
P.currLineRefs=[]
figs=[]
if len(plots)==0: return # nothing to plot
if subPlots:
# compute number of rows and colums for plots we have
subCols=int(round(math.sqrt(len(plots)))); subRows=int(math.ceil(len(plots)*1./subCols))
if wider: subRows,subCols=subCols,subRows
# create a new figure; called once with subPlots, for each subplot without subPlots
def _newFig():
## pylab API
if not noShow: return pylab.figure() # this will go onto the screen; the pylab call sets up the windows as well
else: # with noShow
fig=matplotlib.figure.Figure()
canvas=_HeadlessFigureCanvas(fig) #
return fig
if subPlots: figs=[_newFig()]
for nPlot,p in enumerate(plots.keys()):
pStrip=p.strip().split('=',1)[0]
if not subPlots:
figs.append(_newFig())
axes=figs[-1].add_subplot(1,1,1)
else: axes=figs[-1].add_subplot(subRows,subCols,nPlot+1) # nPlot is 1-based in mpl, for matlab comatibility
axes.grid(True)
if plots[p]==None: # image plot
if not pStrip in list(imgData.keys()): imgData[pStrip]=[]
# fake (empty) image if no data yet
import Image
if len(imgData[pStrip])==0 or imgData[pStrip][-1]==None: img=Image.new('RGBA',(1,1),(0,0,0,0))
else: img=Image.open(imgData[pStrip][-1])
img=axes.imshow(img,origin='upper')
if replace: P.currLineRefs.append(LineRef(line=img,scatter=None,annotation=None,line2=None,xdata=imgData[pStrip],ydata=None,imgData=imgData,dataName=pStrip))
axes.set_axis_off()
continue
plots_p=[addPointTypeSpecifier(o) for o in tuplifyYAxis(plots[p])]
plots_p_y1,plots_p_y2=[],[]; y1=True
missing=set() # missing data columns
if pStrip not in list(data.keys()): missing.add(pStrip if isinstance(pStrip,str) else pStrip.decode('utf-8','ignore'))
for d in plots_p:
d0=d[0]
if d0==None:
y1=False; continue
if not isinstance(d0,(past.builtins.str,str)): raise ValueError('Plots specifiers must be strings (not %s)'%(type(d[0]).__name__))
if '=' in d0: d0=d0.split('=',1)[0]
if y1: plots_p_y1.append((d0,d[1]))
else: plots_p_y2.append((d0,d[1]))
try:
if (
d0 not in list(data.keys())
# and not callable(d[0])
and not (isinstance(d0,str) and (d0.startswith('**') or d0.startswith('*'))) # hack for callable as strings
# and not hasattr(d[0],'keys')
):
missing.add(d0)
except UnicodeEncodeError:
import warnings
warnings.error('UnicodeDecodeError when processing data set '+repr(d[0]))
if missing:
if len(list(data.keys()))==0 or len(data[list(data.keys())[0]])==0: # no data at all yet, do not add garbage NaNs
for m in missing: data[m]=[]
else:
addDataColumns(data,missing)
try:
print('Missing columns in Scene.plot.data, added NaNs:',', '.join([m for m in missing]))
except UnicodeDecodeError:
warnings.warn('UnicodeDecodeError reporting missing data columns -- harmless, just wondering...')
def createLines(pStrip,ySpecs,axes,isY1=True,y2Exists=False):
'''Create data lines from specifications; this code is common for y1 and y2 axes;
it handles y-data specified as callables/dicts passed as string (starting with '*'/'**'), which might create additional lines when updated with liveUpdate.
'''
# save the original specifications; they will be smuggled into the axes object
# the live updated will run yNameFuncs to see if there are new lines to be added
# and will add them if necessary
yNameFuncs=set()
yNames=set()
ySpecs2=[]
for ys in ySpecs:
if not isinstance(ys[0],(past.builtins.str,str)): raise ValueError('Plot specifications must be strings (not a %s).'%type(ys[0]))
if ys[0].startswith('**') or ys[0].startswith('*'):
evEx=eval(ys[0][(2 if ys[0].startswith('**') else 1):],{'S':P.scene})
yNameFuncs.add(evEx) # add callable or dictionary
# XXX: what is ys[1]? Previously, there was no line specifier there for dicts at least
# print evEx,type(evEx), evEx.__iter__(),type(evEx.__iter__())
ySpecs2+=[(ret,ys[1]) for ret in evEx] # traverse list or dict keys
else: ySpecs2.append(ys)
if len(ySpecs2)==0:
print('woo.plot: creating fake plot, since there are no y-data yet')
line,=axes.plot([nan],[nan])
line2,=axes.plot([nan],[nan])
if replace: P.currLineRefs.append(LineRef(line=line,scatter=None,annotation=None,line2=line2,xdata=[nan],ydata=[nan]))
# set different color series for y1 and y2 so that they are recognizable
if 'axes.color_cycle' in matplotlib.rcParams: matplotlib.rcParams['axes.color_cycle']='b,g,r,c,m,y,k' if not isY1 else 'm,y,k,b,g,r,c'
for d in ySpecs2:
yNames.add(d)
# should have been handled above already
#if pStrip not in data:
# print 'Missing column %s in Scene.plot.data, added NaN.'%pString
# addDataColumns(data,[pStrip])
if d[0] not in data:
print('Missing column %s in Scene.plot.data, added NaN.'%d[0])
addDataColumns(data,[d[0]])
line,=axes.plot(data[pStrip],data[d[0]],d[1],label=xlateLabel(d[0],P.labels),**lineKw)
lineKwWithoutAlpha=dict([(k,v) for k,v in list(lineKw.items()) if k!='alpha'])
line2,=axes.plot([],[],d[1],color=line.get_color(),alpha=afterCurrentAlpha,**lineKwWithoutAlpha)
# use (0,0) if there are no data yet
scatterPt=[0,0] if len(data[pStrip])==0 else (data[pStrip][current],data[d[0]][current])
scatterPtPos=[scatterPt[0] if not math.isnan(scatterPt[0]) else 0,scatterPt[1] if not math.isnan(scatterPt[1]) else 0]
# if current value is NaN, use zero instead
scatter=axes.scatter(scatterPtPos[0],scatterPtPos[1],s=scatterSize,color=line.get_color(),**scatterMarkerKw)
if annotateFmt:
if math.isnan(scatterPtPos[0]) or math.isnan(scatterPtPos[1]): text=''
else: text=annotateFmt.format(xy=scatterPt)
annotation=axes.annotate(text,xy=scatterPtPos,color=line.get_color(),**annotateKw)
annotation.annotateFmt=annotateFmt
else: annotation=None
if replace: P.currLineRefs.append(LineRef(line=line,scatter=scatter,annotation=annotation,line2=line2,xdata=data[pStrip],ydata=data[d[0]]))
axes=_my_get_axes(line)
labelLoc=(legendLoc[0 if isY1 else 1] if y2Exists>0 else 'best')
l=axes.legend(loc=labelLoc)
if l:
l.get_frame().set_alpha(legendAlpha)
if hasattr(l,'draggable'): l.draggable(True)
if scientific:
axes.ticklabel_format(style='sci',scilimits=(0,0),axis='both')
# fixes scientific exponent placement for y2: https://sourceforge.net/mailarchive/forum.php?thread_name=20101223174750.GD28779%40ykcyc&forum_name=matplotlib-users
if not isY1: axes.yaxis.set_offset_position('right')
if isY1:
axes.set_ylabel((', '.join([xlateLabel(_p[0],P.labels) for _p in ySpecs2])) if p not in xylabels or not xylabels[p][1] else xylabels[p][1])
axes.set_xlabel(xlateLabel(pStrip,P.labels) if (p not in xylabels or not xylabels[p][0]) else xylabels[p][0])
else:
axes.set_ylabel((', '.join([xlateLabel(_p[0],P.labels) for _p in ySpecs2])) if (p not in xylabels or len(xylabels[p])<3 or not xylabels[p][2]) else xylabels[p][2])
# if there are callable/dict ySpecs, save them inside the axes object, so that the live updater can use those
if yNameFuncs:
axes.wooYNames,axes.wooYFuncs,axes.wooXName,axes.wooLabelLoc=yNames,yNameFuncs,pStrip,labelLoc # prepend woo to avoid clashes
if 0:
# fix missing 'show' method; this has been fixed in matplotlib already, but we need to backport that
# see https://github.com/matplotlib/matplotlib/commit/15fd0ae587a57cb1d7b69546eb359085315148c8
# don't do that for headless backend, error there is fine
fig=axes.get_figure()
if not hasattr(fig,'show'):
mgr=getattr(fig.canvas,'manager')
if mgr: fig.show=lambda *args: mgr.window.show()
createLines(pStrip,plots_p_y1,axes=axes,isY1=True,y2Exists=len(plots_p_y2)>0)
if axesWd>0:
axes.axhline(linewidth=axesWd,color='k')
axes.axvline(linewidth=axesWd,color='k')
# create y2 lines, if any
if len(plots_p_y2)>0:
axes=axes.twinx() # create the y2 axis
createLines(pStrip,plots_p_y2,axes,isY1=False,y2Exists=True)
### scene is not directly accessible from here, do it like this:
S=woo.master.scene
if S.plot==P:
if 'title' in S.tags: axes.set_title(S.tags['title'])
return figs
"""
ha, wa = imga.shape[:2]
hb, wb = imgb.shape[:2]
max_height = np.max([ha, hb])
total_width = wa + wb
new_img = np.zeros(shape=(max_height, total_width, 3))
new_img[:ha, :wa] = imga
new_img[:hb, wa:wa + wb] = imgb
return new_img
def concat_n_images(image_path_list):
"""
Combines N color images from a list of image paths.
"""
output = None
for i, img_path in enumerate(image_path_list):
img = plt.imread(img_path)[:, :, :3]
if i == 0:
output = img
else:
output = concat_images(output, img)
return output
for i in glob.glob('D:/GitHub/GitTesis/RAW DATA/*.img'):
fopen = PIL.open(i)
output = concat_n_images(fopen)
plt.imshow(output)
plt.show()
k[int(gt[i][1]), int(gt[i][0])] = 1
# generate density map
k = gaussian_filter_density(k)
# File path to save density map
file_path = img_path.replace('.jpg', '.h5').replace('images', 'ground')
with h5py.File(file_path, 'w') as hf:
hf['density'] = k
# In[10]:
file_path = img_paths[22].replace('.jpg', '.h5').replace('images', 'ground')
print(file_path)
# In[12]:
#Sample Ground Truth
gt_file = h5py.File(file_path, 'r')
groundtruth = np.asarray(gt_file['density'])
plt.imshow(groundtruth, cmap=CM.jet)
print("Sum = ", np.sum(groundtruth))
# In[13]:
# Image corresponding to the ground truth
img = Image.open(file_path.replace('.h5', '.jpg').replace('ground', 'images'))
plt.imshow(img)
print(file_path.replace('.h5', '.jpg').replace('ground', 'images'))
def createPlots(P,subPlots=True,noShow=False,replace=True,scatterSize=60,wider=False):
'''Create plots based on current data;
:param subPlots: show all plots in one figure as subplots; otherwise, create multiple figures
:param noShow: use headless backend for plots, and do not show plots on the screen
:param replace: do not close existing figures, and do not update P.currLineRefs
'''
import logging
data,imgData,plots,labels,xylabels,legendLoc,axesWd,annotateFmt=P.data,P.imgData,P.plots,P.labels,P.xylabels,P.legendLoc,P.axesWd,P.annotateFmt
if replace:
if P.currLineRefs:
logging.info('Closing existing figures')
ff=set([l.line.get_axes().get_figure() for l in P.currLineRefs]) # get all current figures
for f in ff: pylab.close(f) # close those
P.currLineRefs=[]
figs=[]
if len(plots)==0: return # nothing to plot
if subPlots:
# compute number of rows and colums for plots we have
subCols=int(round(math.sqrt(len(plots)))); subRows=int(math.ceil(len(plots)*1./subCols))
if wider: subRows,subCols=subCols,subRows
# create a new figure; called once with subPlots, for each subplot without subPlots
def _newFig():
## pylab API
if not noShow: return pylab.figure() # this will go onto the screen; the pylab call sets up the windows as well
else: # with noShow
fig=matplotlib.figure.Figure()
canvas=_HeadlessFigureCanvas(fig) #
return fig
if subPlots: figs=[_newFig()]
for nPlot,p in enumerate(plots.keys()):
pStrip=p.strip().split('=',1)[0]
if not subPlots:
figs.append(_newFig())
axes=figs[-1].add_subplot(1,1,1)
else: axes=figs[-1].add_subplot(subRows,subCols,nPlot+1) # nPlot is 1-based in mpl, for matlab comatibility
axes.grid(True)
if plots[p]==None: # image plot
if not pStrip in imgData.keys(): imgData[pStrip]=[]
# fake (empty) image if no data yet
import Image
if len(imgData[pStrip])==0 or imgData[pStrip][-1]==None: img=Image.new('RGBA',(1,1),(0,0,0,0))
else: img=Image.open(imgData[pStrip][-1])
img=axes.imshow(img,origin='upper')
if replace: P.currLineRefs.append(LineRef(line=img,scatter=None,annotation=None,line2=None,xdata=imgData[pStrip],ydata=None,imgData=imgData,dataName=pStrip))
axes.set_axis_off()
continue
plots_p=[addPointTypeSpecifier(o) for o in tuplifyYAxis(plots[p])]
plots_p_y1,plots_p_y2=[],[]; y1=True
missing=set() # missing data columns
if pStrip not in data.keys(): missing.add(pStrip.decode('utf-8','ignore'))
for d in plots_p:
if d[0]==None:
y1=False; continue
if not isinstance(d[0],(str,unicode)): raise ValueError('Plots specifiers must be strings (not %s)'%(type(d[0]).__name__))
if y1: plots_p_y1.append(d)
else: plots_p_y2.append(d)
try:
if (
d[0] not in data.keys()
# and not callable(d[0])
and not (isinstance(d[0],(str,unicode)) and (d[0].startswith('**') or d[0].startswith('*'))) # hack for callable as strings
# and not hasattr(d[0],'keys')
):
missing.add(d[0])
except UnicodeEncodeError:
import warnings
warnings.error('UnicodeDecodeError when processing data set '+repr(d[0]))
if missing:
if len(data.keys())==0 or len(data[data.keys()[0]])==0: # no data at all yet, do not add garbage NaNs
for m in missing: data[m]=[]
else:
addDataColumns(data,missing)
try:
print 'Missing columns in Scene.plot.data, added NaNs:',', '.join([m.encode('utf-8') for m in missing])
except UnicodeDecodeError:
warnings.warn('UnicodeDecodeError reporting missing data columns -- harmless, just wondering...')
def createLines(pStrip,ySpecs,axes,isY1=True,y2Exists=False):
'''Create data lines from specifications; this code is common for y1 and y2 axes;
it handles y-data specified as callables/dicts passed as string (starting with '*'/'**'), which might create additional lines when updated with liveUpdate.
'''
# save the original specifications; they will be smuggled into the axes object
# the live updated will run yNameFuncs to see if there are new lines to be added
# and will add them if necessary
yNameFuncs=set()
yNames=set()
ySpecs2=[]
for ys in ySpecs:
if not isinstance(ys[0],(str,unicode)): raise ValueError('Plot specifications must be strings (not a %s).'%type(ys[0]))
if ys[0].startswith('**') or ys[0].startswith('*'):
evEx=eval(ys[0][(2 if ys[0].startswith('**') else 1):],{'S':P.scene})
yNameFuncs.add(evEx) # add callable or dictionary
# XXX: what is ys[1]? Previously, there was no line specifier there for dicts at least
# print evEx,type(evEx), evEx.__iter__(),type(evEx.__iter__())
ySpecs2+=[(ret,ys[1]) for ret in evEx] # traverse list or dict keys
else: ySpecs2.append(ys)
if len(ySpecs2)==0:
print 'woo.plot: creating fake plot, since there are no y-data yet'
line,=axes.plot([nan],[nan])
line2,=axes.plot([nan],[nan])
if replace: P.currLineRefs.append(LineRef(line=line,scatter=None,annotation=None,line2=line2,xdata=[nan],ydata=[nan]))
# set different color series for y1 and y2 so that they are recognizable
if matplotlib.rcParams.has_key('axes.color_cycle'): matplotlib.rcParams['axes.color_cycle']='b,g,r,c,m,y,k' if not isY1 else 'm,y,k,b,g,r,c'
for d in ySpecs2:
yNames.add(d)
# should have been handled above already
#if pStrip not in data:
# print 'Missing column %s in Scene.plot.data, added NaN.'%pString
# addDataColumns(data,[pStrip])
if d[0] not in data:
print 'Missing column %s in Scene.plot.data, added NaN.'%d[0]
addDataColumns(data,[d[0]])
line,=axes.plot(data[pStrip],data[d[0]],d[1],label=xlateLabel(d[0],P.labels),**lineKw)
lineKwWithoutAlpha=dict([(k,v) for k,v in lineKw.items() if k!='alpha'])
line2,=axes.plot([],[],d[1],color=line.get_color(),alpha=afterCurrentAlpha,**lineKwWithoutAlpha)
# use (0,0) if there are no data yet
scatterPt=[0,0] if len(data[pStrip])==0 else (data[pStrip][current],data[d[0]][current])
scatterPtPos=[scatterPt[0] if not math.isnan(scatterPt[0]) else 0,scatterPt[1] if not math.isnan(scatterPt[1]) else 0]
# if current value is NaN, use zero instead
scatter=axes.scatter(scatterPtPos[0],scatterPtPos[1],s=scatterSize,color=line.get_color(),**scatterMarkerKw)
if annotateFmt:
if math.isnan(scatterPtPos[0]) or math.isnan(scatterPtPos[1]): text=''
else: text=annotateFmt.format(xy=scatterPt)
annotation=axes.annotate(text,xy=scatterPtPos,color=line.get_color(),**annotateKw)
annotation.annotateFmt=annotateFmt
else: annotation=None
if replace: P.currLineRefs.append(LineRef(line=line,scatter=scatter,annotation=annotation,line2=line2,xdata=data[pStrip],ydata=data[d[0]]))
axes=line.get_axes()
labelLoc=(legendLoc[0 if isY1 else 1] if y2Exists>0 else 'best')
l=axes.legend(loc=labelLoc)
if l:
l.get_frame().set_alpha(legendAlpha)
if hasattr(l,'draggable'): l.draggable(True)
if scientific:
axes.ticklabel_format(style='sci',scilimits=(0,0),axis='both')
# fixes scientific exponent placement for y2: https://sourceforge.net/mailarchive/forum.php?thread_name=20101223174750.GD28779%40ykcyc&forum_name=matplotlib-users
if not isY1: axes.yaxis.set_offset_position('right')
if isY1:
axes.set_ylabel((', '.join([xlateLabel(_p[0],P.labels) for _p in ySpecs2])) if p not in xylabels or not xylabels[p][1] else xylabels[p][1])
axes.set_xlabel(xlateLabel(pStrip,P.labels) if (p not in xylabels or not xylabels[p][0]) else xylabels[p][0])
else:
axes.set_ylabel((', '.join([xlateLabel(_p[0],P.labels) for _p in ySpecs2])) if (p not in xylabels or len(xylabels[p])<3 or not xylabels[p][2]) else xylabels[p][2])
# if there are callable/dict ySpecs, save them inside the axes object, so that the live updater can use those
if yNameFuncs:
axes.wooYNames,axes.wooYFuncs,axes.wooXName,axes.wooLabelLoc=yNames,yNameFuncs,pStrip,labelLoc # prepend woo to avoid clashes
if 0:
# fix missing 'show' method; this has been fixed in matplotlib already, but we need to backport that
# see https://github.com/matplotlib/matplotlib/commit/15fd0ae587a57cb1d7b69546eb359085315148c8
# don't do that for headless backend, error there is fine
fig=axes.get_figure()
if not hasattr(fig,'show'):
mgr=getattr(fig.canvas,'manager')
if mgr: fig.show=lambda *args: mgr.window.show()
createLines(pStrip,plots_p_y1,axes=axes,isY1=True,y2Exists=len(plots_p_y2)>0)
if axesWd>0:
axes.axhline(linewidth=axesWd,color='k')
axes.axvline(linewidth=axesWd,color='k')
# create y2 lines, if any
if len(plots_p_y2)>0:
axes=axes.twinx() # create the y2 axis
createLines(pStrip,plots_p_y2,axes,isY1=False,y2Exists=True)
### scene is not directly accessible from here, do it like this:
S=woo.master.scene
if S.plot==P:
if 'title' in S.tags: axes.set_title(S.tags['title'])
return figs
#Play Video
import cv2
import mediapipe as mp
import streamlit as st
mp_drawing = mp.solutions.drawing_utils
mp_hands = mp.solutions.hands
y=["image"]
temp_status = len(os.listdir("image"))
#img = None
uploaded_file = st.file_uploader("Alternatively upload a file")
if uploaded_file is not None:
img = Image.open(uploaded_file)
img.save("image/hands.jpg")
st.success("Uploaded.")
# For static images:
hands = mp_hands.Hands(
static_image_mode=True,
max_num_hands=2,
min_detection_confidence=0.5)
st.write("Raw image")
try:
st.image(img, use_column_width=True)
except NameError:
pass
image = Image.fromarray(255 * k)
# image.show()
# File path to save density map
file_path = img_path.replace('.jpg', '.h5').replace('images', 'ground')
with h5py.File(file_path, 'w') as hf:
hf['density'] = k
# %%
path_test = "G:/pycharm/CSRnet-master/data/part_A_final/train_data/ground/IMG_107.h5"
# file_path = img_paths[-5].replace('.jpg','.h5').replace('images','ground')
file_path = path_test
print(file_path)
# %%
# Sample Ground Truth
gt_file = h5py.File(file_path, 'r')
groundtruth = np.asarray(gt_file['density'])
plt.imshow(groundtruth, cmap=CM.jet)
print("Sum = ", np.sum(groundtruth))
# %%
# Image corresponding to the ground truth
img = Image.open(file_path.replace('.h5',
'.jpg').replace('ground',
'images')).convert('RGBA')
plt.imshow(img)
print(file_path.replace('.h5', '.jpg').replace('ground', 'images'))
import PIL as Image
pil_im = Image.open('C:\\Users\\Arsalan\\Desktop\\myprogress.PNG')
print(pil_im)
