def get_domain_color(image):
# returns: (R, G, B) tuple
dominant = Haishoku.getDominant(image)
color = "red"
redsimi = math.sqrt((dominant[0] - 255) * (dominant[0] - 255) +
dominant[1] * dominant[1] + dominant[2] * dominant[2])
greensimi = math.sqrt(dominant[0] * dominant[0] + (dominant[1] - 255) *
(dominant[1] - 255) + dominant[2] * dominant[2])
if (greensimi < redsimi):
color = "green"
return color
def saveDominant(image_path, path, idx):
# get the dominant color
dominant = Haishoku.getDominant(image_path)
# generate colors boxes
images = []
dominant_box = new_image('RGB', (50, 20), dominant)
for i in range(8):
images.append(dominant_box)
# save dominant color
joint_image(images, path, idx, 'Dominant')
def main():
path = "/Users/wujianming/Desktop/WechatIMG18547.jpeg"
# path = "http://wx2.sinaimg.cn/large/89243dfbly1ffoekfainzj20dw05k0u7.jpg"
# getPalette api
palette = Haishoku.getPalette(path)
# getDominant api
dominant = Haishoku.getDominant(path)
# showPalette api
Haishoku.showPalette(path)
# showDominant api
# Haishoku.showDominant(path)
# Haishoku object
h = Haishoku.loadHaishoku(path)
print(h.palette)
print(h.dominant)
def main():
path = "demo_01.png"
# getPalette api
palette = Haishoku.getPalette(path)
print(palette)
# getDominant api
dominant = Haishoku.getDominant(path)
print(dominant)
# showPalette api
Haishoku.showPalette(path)
# showDominant api
Haishoku.showDominant(path)
# Haishoku object
h = Haishoku.loadHaishoku(path)
print(h.image)
print(h.palette)
print(h.dominant)
def main():
url = "https://img3.doubanio.com/lpic/s27028282.jpg"
r = requests.get(url)
path = BytesIO(r.content)
# getPalette api
palette = Haishoku.getPalette(path)
print(palette)
# getDominant api
dominant = Haishoku.getDominant(path)
print(dominant)
# showPalette api
Haishoku.showPalette(path)
# showDominant api
Haishoku.showDominant(path)
# Haishoku object
h = Haishoku.loadHaishoku(path)
print(h.palette)
print(h.dominant)
def palette_op(self, palette_size, sample_factor=4):
"""Generates an shmops.fill_operation obj"""
print("||||| Initiating Palette Fill Operation |||||")
fill_op = shmops.Fill_Operation(id='4321')
tiles = self.slice_to_tiles(show_info="Image to Map")
#get palette to be used in the process
if sample_factor == 1:
palette = palette.generate(self.path,
palette_size,
debug=self.debug)
else:
#get combined palette by slicing map into sample tiles
sampling_map_size = self.get_map_size(sample_factor)
palette = self.get_combined_palette(palette_size,
sampling_map_size)
temp_path = Path('temp_img.png')
x, y = 0, 0
for row in progress_bar.progress_bar(tiles, "Processing Map: ",
" Row: ", 36):
for tile in row:
#if self.debug:
# temp_path = f'{x}x{y}y_temp_img.png'
# temp_path = Path('./test_tiles/' + temp_path)
tile.save(temp_path, "PNG")
dominant = Haishoku.getDominant(str(temp_path))
tile_color = palette.nearest_color(palette, dominant)
#if self.debug: print(f'Tile Address: {x}, {y} | Tile Color: {tile_color} | Saved to: {temp_path}')
fill_op.add_fill(x, y, palette.rgb_to_hex(*tile_color))
x += 1
y += 1
x = 0
if not self.debug: temp_path.unlink()
return fill_op
def buildingDatabase(jpg_dir, wav_path):
# 超参数
jpg_dir = jpg_dir
image_files = os.listdir(jpg_dir)
image_files.sort(key=lambda x: int(x.split('.')[0][5:]))
# 纹理检测
dhashList = []
# dominant color
Hlist = []
# Slist=[]
Vlist = []
# motion; optical flow
# 角点检测参数
feature_params = dict(maxCorners=100,
qualityLevel=0.1,
minDistance=7,
blockSize=7)
# KLT光流参数
lk_params = dict(winSize=(15, 15),
maxLevel=2,
criteria=(cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT,
10, 0.02))
tracks = []
track_len = 15
detect_interval = 5
beforeGrey = None
MotionList = []
count = 0
# for i in range(0,480):
for jpg_path in image_files[0:480]:
# jpg_path=jpg_dir+"frame"+str(i)+".jpg"
jpg_path = jpg_dir + jpg_path
print(jpg_path)
# dominant color
d_color = Haishoku.getDominant(jpg_path)
#print(count, ':', d_color)
r = d_color[0]
g = d_color[1]
b = d_color[2]
# 转换为HSV空间
cmax = max(max(r, g), b)
cmin = min(min(r, g), b)
delta = cmax - cmin
V = cmax
if cmax == 0:
S = 0
else:
S = delta / cmax
if delta == 0:
H = 0
elif cmax == r:
H = ((g - b) / delta) * 60
elif cmax == g:
H = 120 + ((b - r) / delta) * 60
else:
H = 240 + ((r - g) / delta) * 60
if H < 0:
H = H + 360
Hlist.append(H)
# Slist.append(S)
Vlist.append(V)
img = cv2.imread(jpg_path)
# 纹理特征
dhash = d_hash(img)
dhashList.append(dhash)
# motion
curGrey = next = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
img0, img1 = beforeGrey, curGrey
p0 = np.float32([tr[-1] for tr in tracks]).reshape(-1, 1, 2)
if len(tracks) > 0:
img0, img1 = beforeGrey, curGrey
p0 = np.float32([tr[-1] for tr in tracks]).reshape(-1, 1, 2)
# 上一帧的角点和当前帧的图像作为输入来得到角点在当前帧的位置
p1, st, err = cv2.calcOpticalFlowPyrLK(img0, img1, p0, None,
**lk_params)
sum = 0.0
for i in range(0, len(p0)):
dist = math.sqrt((p0[i][0][0] - p1[i][0][0])**2 +
(p0[i][0][1] - p1[i][0][1])**2)
sum = sum + dist
avg = sum / len(p0)
MotionList.append(avg)
# 反向检查,当前帧跟踪到的角点及图像和前一帧的图像作为输入来找到前一帧的角点位置
p0r, _, _ = cv2.calcOpticalFlowPyrLK(img1, img0, p1, None,
**lk_params)
# 得到角点回溯与前一帧实际角点的位置变化关系
d = abs(p0 - p0r).reshape(-1, 2).max(-1)
# 判断d内的值是否小于1，大于1跟踪被认为是错误的跟踪点
good = d < 1
new_tracks = []
for i, (tr, (x, y),
flag) in enumerate(zip(tracks, p1.reshape(-1, 2), good)):
# 判断是否为正确的跟踪点
if not flag:
continue
# 存储动态的角点
tr.append((x, y))
# 只保留track_len长度的数据，消除掉前面的超出的轨迹
if len(tr) > track_len:
del tr[0]
# 保存在新的list中
new_tracks.append(tr)
# 更新特征点
tracks = new_tracks
else:
MotionList.append(0.0)
# 每隔 detect_interval 时间检测一次特征点
if count % detect_interval == 0:
mask = np.zeros_like(curGrey)
mask[:] = 255
p = cv2.goodFeaturesToTrack(curGrey, mask=mask, **feature_params)
if p is not None:
for x, y in np.float32(p).reshape(-1, 2):
tracks.append([(x, y)])
beforeGrey = curGrey
count += 1
# 得到整个视频的dominant color
print('H len:', len(Hlist))
print('Hlist:', Hlist)
# print('S len:',len(Slist))
# print('Slist:',Slist)
print('V len:', len(Vlist))
print('Vlist:', Vlist)
# 纹理
print('hash len:', len(dhashList))
print('hash list:', dhashList)
# Motion
print('Motion len:', len(MotionList))
print('MotionList:', MotionList)
#voice
voiceValue = get_voice_descriptor(wav_path)
print('voiceValue:', voiceValue)
return Hlist, Vlist, MotionList, dhashList, voiceValue
def music():
w = 490*2
h = 740*2
banner_w = 490*2
banner_h = 235*2
cover_w = 140*2
cover_h = 140*2
cover_top = 120*2
cover_left = 100*2
block_w = 32*2
block_h = 12*2
block_left = 97*2
block_top = 160*2 + banner_h
max_content_w = 300*2
max_title_w = 190*2
title_left = cover_w + cover_left + 10 *2
title = '成都'
title_font = ImageFont.truetype('font/zh/YueSong.ttf',28*2)
single_title_w,single_title_h= title_font.getsize("已")
titles = list(title)
title_formated = ''
temp = ''
for word in titles:
temp += word
temp_w,temp_h = title_font.getsize(temp)
title_formated += word
if temp_w > max_title_w + single_title_w:
title_formated += '\n'
temp = ''
tlines = len(title_formated.split('\n'))
title_h = tlines * single_title_h + (tlines -1) * 28*2
title_top = banner_h - title_h - 10 *2
max_author_w = 190*2
author_left = cover_w + cover_left+ 10 *2
author_top = banner_h + 10 *2
author = '赵雷'
author_font = ImageFont.truetype('font/zh/YueSong.ttf',14*2)
single_author_w,single_author_h = author_font.getsize("已")
authors = list(author)
author_formated = ''
temp = ''
for word in authors:
temp += word
temp_w,temp_h = author_font.getsize(temp)
author_formated += word
if temp_w > max_author_w + single_author_w:
author_formated += '\n'
temp = ''
alines = len(author_formated.split('\n'))
author_h = alines * single_author_h + (alines -1) * 14*2
content_left = 95*2
content_top = banner_h + 150*2
content = 'Just let time go on\n让我 掉下眼泪的\n不止昨夜的酒\n让我依依不舍的\n不止你的温柔\n余路还要走多久\n你攥着我的手\n让我感到为难的\n是挣扎的自由'
content_formated = ''
content_font = ImageFont.truetype('font/zh/YueSong.ttf',18*2)
single_content_w,single_content_h = content_font.getsize("已")
lines = content.split('\n')
for line in lines:
contents = list(line)
line_formated = ''
temp = ''
for word in contents:
temp += word
temp_w,temp_h = content_font.getsize(temp)
line_formated += word
if temp_w > max_content_w + single_content_w:
line_formated += '\n'
temp = ''
if temp != '':
line_formated += '\n'
content_formated += line_formated
print(content_formated)
clines = len(content_formated.split('\n'))
content_h = clines * single_author_h + (clines -1) * 14*2
h = max(h,content_top + content_h + 100*2)
base = Image.new('RGBA',(w,h),(255,255,255,255))
url = "https://y.gtimg.cn/music/photo_new/T002R300x300M000001qHmKU29WX7K.jpg"
file = BytesIO(requests.get(url).content)
photo = Image.open(file).convert('RGBA')
(pw, ph) = photo.size
r,g,b = Haishoku.getDominant(file)
if pw/ph>w/h:
bbox = ((pw-ph*w/h)/2,0,(pw+ph*w/h)/2,ph)
else:
bbox = (0,(ph-pw*h/w)/2,pw,(ph+pw*h/w)/2)
txt = Image.new('L', (w,h), 255)
draw = ImageDraw.Draw(txt)
alpha = Image.new('L', (w,h), 0)
draw.multiline_text((title_left,title_top), title_formated, font=title_font, fill=0, align='left',spacing=15*2)
draw.multiline_text((author_left,author_top), author_formated, font=author_font, fill=0, align='left',spacing=15*2)
draw.multiline_text((content_left,content_top), content_formated, font=content_font, fill=0, align='left',spacing=12*2)
alpha.paste(txt, (0, 0))
banner_cover = photo.crop(bbox)
banner_cover = banner_cover.resize((w,h),Image.ANTIALIAS)
banner_blur = banner_cover.filter(ImageFilter.GaussianBlur(80))
banner_wrap = Image.new('RGBA',(w,h),(255, 255, 255, 193))
banner_mask = Image.alpha_composite(banner_blur,banner_wrap)
banner_mask.putalpha(alpha)
banner_blur.paste(banner_mask,box=(0,0),mask=banner_mask)
base.paste(banner_blur,box=(0,0))
if pw/ph>cover_w/cover_h:
box = ((pw-ph*cover_w/cover_h)/2,0,(pw+ph*cover_w/cover_h)/2,ph)
else:
box = (0,(ph-pw*cover_h/cover_w)/2,pw,(ph+pw*cover_h/cover_w)/2)
cover = photo.crop(box)
cover = cover.resize((cover_w,cover_h),Image.ANTIALIAS)
base.paste(cover,box=(cover_left,cover_top))
base.show()
def book(request):
w = 490*2
h = 740*2
banner_w = 490*2
banner_h = 265*2
cover_w = 135*2
cover_h = 200*2
cover_top = 120*2
cover_left = int((w-cover_w)/2)
block_w = 32*2
block_h = 12*2
block_left = 97*2
block_top = 160*2 + banner_h
max_content_w = 310*2
title_left = 97*2
title_top = block_top+block_h+20*2
title = '高窗'
title_font = ImageFont.truetype('font/zh/YueSong.ttf',28*2)
single_title_w,single_title_h= title_font.getsize("已")
titles = wrap(title, 1)
title_formated = ''
temp = ''
for word in titles:
temp += word
temp_w,temp_h = title_font.getsize(temp)
title_formated += word
if temp_w > max_content_w + single_title_w:
title_formated += '\n'
temp = ''
tlines = len(title_formated.split('\n'))
title_h = tlines * single_title_h + (tlines -1) * 28*2
division_left = 97*2
division_top = title_top+single_title_h+12*2
division = '╱'
division_font = ImageFont.truetype('font/zh/PingFang.ttf',20*2)
single_division_w,single_division_h = division_font.getsize("已")
author_left = 97*2
author_top = division_top + title_h
author = '作者：雷蒙德.钱德勒'
author_font = ImageFont.truetype('font/zh/YueSong.ttf',14*2)
single_author_w,single_author_h = author_font.getsize("已")
authors = wrap(author, 1)
author_formated = ''
temp = ''
for word in authors:
temp += word
temp_w,temp_h = author_font.getsize(temp)
author_formated += word
if temp_w > max_content_w + single_author_w:
author_formated += '\n'
temp = ''
alines = len(author_formated.split('\n'))
author_h = alines * single_author_h + (alines -1) * 14*2
content_left = 97*2
content_top = author_top + author_h + 12*2
content = '故事原型：加州石油大亨爱德华.多赫尼之子被杀案，及蒂波特山油田丑闻'
content_formated = ''
content_font = ImageFont.truetype('font/zh/YueSong.ttf',14*2)
single_content_w,single_content_h = content_font.getsize("已")
contents = wrap(content, 1)
temp = ''
for word in contents:
temp += word
temp_w,temp_h = content_font.getsize(temp)
content_formated += word
if temp_w > max_content_w + single_content_w:
content_formated += '\n'
temp = ''
print(content_formated)
clines = len(content_formated.split('\n'))
content_h = clines * single_author_h + (clines -1) * 14*2
h = content_top + content_h + 150*2
base = Image.new('RGBA',(w,h),(255,255,255,255))
draw = ImageDraw.Draw(base)
draw.rectangle([(0,0),(banner_w,banner_h)],(26, 26, 26, 255))
url = "https://img3.doubanio.com/lpic/s27028282.jpg"
file = BytesIO(requests.get(url).content)
photo = Image.open(file).convert('RGBA')
(pw, ph) = photo.size
if pw/ph>cover_w/cover_h:
box = ((pw-ph*cover_w/cover_h)/2,0,(pw+ph*cover_w/cover_h)/2,ph)
else:
box = (0,(ph-cover_w*cover_h/cover_w)/2,pw,(ph+pw*cover_h/cover_w)/2)
photo = photo.crop(box)
photo = photo.resize((cover_w,cover_h),Image.ANTIALIAS)
base.paste(photo,box=(cover_left,cover_top))
dominant = Haishoku.getDominant(file)
draw.rectangle([(block_left,block_top),(block_left+block_w,block_top+block_h)],dominant)
draw.multiline_text((title_left,title_top), title_formated, font=title_font, fill=(70,70,70), align='left',spacing=15*2)
draw.multiline_text((division_left,division_top), division, font=division_font, fill=(70,70,70), align='left',spacing=0)
draw.multiline_text((author_left,author_top), author_formated, font=author_font, fill=(90,90,90), align='left',spacing=15*2)
draw.multiline_text((content_left,content_top), content_formated, font=content_font, fill=(90,90,90), align='left',spacing=12*2)
print(dominant)
#base.show()
# get BytesIO
msstream = BytesIO()
# save image data to output stream
base.save(msstream,"jpeg")
# release memory
base.close()
return HttpResponse(msstream.getvalue(),content_type="image/jpeg")
def get_dominant_color(image):
dominant_color = Haishoku.getDominant(image)
return dominant_color
def haishokuColor(img):
dominant = Haishoku.getDominant(img)
print(dominant)
palette = Haishoku.getPalette(img)
print(palette)
import os
import csv
sys.path.insert(0, "..")
from haishoku.haishoku import Haishoku
folder = "/Users/talamram/Downloads/thike/"
# Count files in selected repository
counter = 0
for file in os.listdir('..'):
counter += 1
print(str(counter) + 'files counted!')
# Iterate through images in folder and extract dominant colour and palette
# and write them to a csv
path = "test.JPG"
# getPalette api
palette = Haishoku.getPalette(path)
# getDominant api
dominant = Haishoku.getDominant(path)
# Haishoku object
h = Haishoku.loadHaishoku(path)
print('= showpalette =')
print(h.palette)
print('= dominant =')
print(h.dominant)
# from colorthief import ColorThief from haishoku.haishoku import Haishoku image = './1341543305665_.pic_hd.jpg' # image = './1331543305664_.pic_hd.jpg' dominant = Haishoku.getDominant(image) print(dominant) # Haishoku.showDominant( image ) palette = Haishoku.getPalette(image) print(palette) # Haishoku.showPalette( image )
def getColor(self, imagePath):
dominant = Haishoku.getDominant(imagePath)
color = dominant.__str__().replace('(', '').replace(')', '')
print('--------------------> getColor(%s) = %s' % (imagePath, color))
return color
