Python Image.caption方法代码示例

# 需要导入模块: from wand.image import Image [as 别名]
# 或者: from wand.image.Image import caption [as 别名]
	def make_image_to_post(self, job_string, image, image_format):
		font_size_to_width_ratio = 0.061
		font_location = './Gotham-Bold.otf'
		fontColors = ['white', 'black']

		logging.info(str(datetime.now()) + ': Begin image compositing.')

		try:
			im = Image(blob=image)
		except MissingDelegateError as e:
			raise
		except:
			raise

		font_size = im.width * font_size_to_width_ratio

		im_clone = im.clone()
		im_clone.resize(1,1)
		
		for row in im_clone:
			for col in row:
				assert isinstance(col, Color)
				if (col.red + col.green + col.blue) / 3.0 >= 0.5:
					fontColors.reverse()

		font = Font(font_location, size=font_size, color=Color(fontColors[1]))
		im.caption(job_string, left=7, top=7, width=im.width-10, height=im.height-10, font=font)
		font = Font(font_location, size=font_size, color=Color(fontColors[0]))
		im.caption(job_string, left=5, top=5, width=im.width-10, height=im.height-10, font=font)

		im.format = image_format
		return im

# 需要导入模块: from wand.image import Image [as 别名]
# 或者: from wand.image.Image import caption [as 别名]
def genTextPNG(text,font="/usr/share/fonts/type1/gsfonts/c059016l.pfb",fsize=48):
	#put these here so that they are not imported until needed
	from wand.image import Image
	from wand.font import Font
	from wand.color import Color

	# convert -size 1000x180 xc:transparent -fx 0 -channel A -fx 'cos(0.6*pi*(i/w-0.5))-0.0' background.png
	img=Image(filename="background1280.png")
	fontwhite=Font(path=font,color=Color("white"),size=fsize,antialias=True)
	fontblack=Font(path=font,color=Color("black"),size=fsize,antialias=True)
	img.caption(text,font=fontblack,gravity='center',left=8,top=8)
	img.caption(text,font=fontwhite,gravity='center')
	final = Image(width=1280,height=720)
	final.composite(img,0,530)
	return final

# 需要导入模块: from wand.image import Image [as 别名]
# 或者: from wand.image.Image import caption [as 别名]
def create_row(imgs, offsets, gap, fixed_width=0, caption=None, caption_offset=(0,0)):
	row_width = 0
	i = 0
	row_height = 0

	for img in imgs:
		if isinstance(img, Image):
			row_width += img.width + gap
			row_height = max(img.height, row_height)
		else:
			row_width += offsets[i][0] + gap
		i += 1

	if fixed_width:
		row_width = fixed_width

	row = Image(width=row_width, height=row_height)

	i = 0
	x = 0

	for img in imgs:
		if isinstance(img, Image):
			row.composite(img, left=x + offsets[i], top=(row_height - img.height) / 2)
			x += img.width + offsets[i] + gap
		else:
			(offset_x, offset_y, width, font) = offsets[i]
			row.caption(img, left=x + offset_x, top=offset_y, width=250, height=250, font=font)
			x += width + gap
		i += 1

	if caption:
		caption_font = Font(path="%s/source-code-pro/SourceCodePro-Medium.otf" % args.fonts, size=14)
		row_w_caption = Image(width=row_width, height=row_height+20)
		row_w_caption.caption(caption, left=caption_offset[0], top=caption_offset[1],
								width=1450, height=50, font=caption_font)
		row_w_caption.composite(row, left=0, top=20)
		return row_w_caption
	else:
		return row

# 需要导入模块: from wand.image import Image [as 别名]
# 或者: from wand.image.Image import caption [as 别名]
        pages = 1
        
        image = Image(
            width = imageFromPdf.width,
            height = imageFromPdf.height*pages          
           
        )
        
        for i in range(pages):
            image.composite(
                imageFromPdf.sequence[i],
                top = imageFromPdf.height * i,
                left = 0
            )
            
        image.resize(250,250)
        image.alpha_channel = False
        image.format = 'png'
        print(image.size)
        image.background_color = Color('pink')
        
        image.type = 'grayscale'
        image.caption = file.split('.')[0]
        image.save(filename = fileDirectory+file.split('.')[0]+".png")

        image.clear()
        image.close()

        #display(image)

# 需要导入模块: from wand.image import Image [as 别名]
# 或者: from wand.image.Image import caption [as 别名]
def compose_adaptive_prey(img_paths=None, match_json=None, gap=5, horizontal_gap=5, description=None, caption="Catcierge"):

	img = Image(width=600, height=1124, background=Color("#8A968E"))

	#print("Font path: %s" % args.fonts)

	font = Font(path="%s/source-code-pro/SourceCodePro-Medium.otf" % args.fonts, size=64)
	font_title = Font(path="%s/alex-brush/AlexBrush-Regular.ttf" % args.fonts, size=64)
	font_math = Font(path="%s/Asana-Math/Asana-Math.otf" % args.fonts, size=64)


	imgs = []
	assert (img_paths and (len(img_paths) > 0)) or match_json, \
		"Missing either a list of input image paths or a match json"

	if not img_paths or len(img_paths) == 0:
		step_count = match_json["step_count"]

		for step in match_json["steps"][:step_count]:
			print("Step: %s" % step["name"])
			img_paths.append(step["path"])

	# TODO: Allow any matcher type and number of images...	
	assert len(img_paths) == 1 or len(img_paths) == 11, \
		"Invalid number of images %d, expected 2 or 11" % len(img_paths)

	for img_path in img_paths:
		#print img_path
		imgs.append(Image(filename=img_path))

	mpos = lambda w: (img.width - w) / 2

	if len(img_paths) == 1:
		img.caption(caption, left=(img.width - 250) / 2, top=5, width=250, height=100, font=font_title)
		img.composite(imgs[0], left=mpos(imgs[0].width), top=120)
		return img

	orgimg = imgs[0]	# Original image.
	detected = imgs[1]	# Detected cat head roi. 
	croproi = imgs[2]	# Cropped/extended roi.
	globalthr = imgs[3]	# Global threshold (inverted).
	adpthr = imgs[4]	# Adaptive threshold (inverted).
	combthr = imgs[5]	# Combined threshold.
	opened = imgs[6]	# Opened image.
	dilated = imgs[7]	# Dilated image.
	combined = imgs[8]	# Combined image (re-inverted).
	contours = imgs[9]	# Contours of white areas.
	final = imgs[10]	# Final image.
	
	# TODO: Enable creating these based on input instead.
	kernel3x3 = create_kernel(w=3, h=3)
	kernel2x2 = create_kernel(w=2, h=2)
	kernel5x1 = create_kernel(w=5, h=1)

	x_start = 20

	img.caption(caption, left=(img.width - 250) / 2, top=5, width=250, height=100, font=font_title)

	if description:
		desc_font = Font(path="%s/source-code-pro/SourceCodePro-Medium.otf" % args.fonts, size=24)
		text_width = (desc_font.size) * int(len(description) * 0.7)
		img.caption(description, left=(img.width - text_width) / 2, top=80, width=text_width, height=100, font=desc_font)

	height = 120

	# Original.
	img.composite(orgimg, left=mpos(orgimg.width), top=height) 
	height += orgimg.height + gap
	
	# Detected head + cropped region of interest.
	head_row = create_row([detected, croproi], [0, 0], horizontal_gap, caption="Detected head  Cropped ROI")
	img.composite(head_row, left=mpos(head_row.width), top=height)
	height += head_row.height + gap

	# TODO: simplify the code below by making the symbols into images before they're used to create the rows.

	# Combine the threshold images.
	thr_row = create_row([globalthr, "+", adpthr, "=", combthr],
						[x_start,
						(4 * horizontal_gap, -15, 14 * horizontal_gap, font),
						0,
						(2 * horizontal_gap, -15, 8 * horizontal_gap, font),
						2 * horizontal_gap],
						horizontal_gap, fixed_width=img.width,
						caption="Global Threshold           Adaptive Threshold       Combined Threshold",
						caption_offset=(x_start, 0))
	img.composite(thr_row, left=mpos(thr_row.width), top=height)
	height += thr_row.height + gap

	# Open the combined threshold.
	open_row = create_row([combthr, u"∘", kernel2x2, "=", opened],
						[x_start,
						(5 * horizontal_gap, -5, 14 * horizontal_gap, font_math),
						0,
						(21 * horizontal_gap, -15, 10 * horizontal_gap, font),
						19 * horizontal_gap + 3],
						horizontal_gap, fixed_width=img.width,
						caption="Combined Threshold         2x2 Kernel               Opened Image",
						caption_offset=(x_start, 0))
	img.composite(open_row, left=mpos(open_row.width), top=height)
#.........这里部分代码省略.........