Matches in Nanopublications for { ?s <http://purl.org/dc/terms/description> ?o ?g. }
- step description "@is_fairstep(label='Convert the image') def convert_image(img): from PIL import Image return img.convert('LA') " assertion.
- step description "@is_fairstep(label='awesome smoothening of an image') # Give it your own name: def my_awesome_step(image): from PIL import Image # new_image = .... smoothenedImage = image.filter(ImageFilter.SMOOTH) new_image = image.filter(ImageFilter.SMOOTH_MORE) return new_image " assertion.
- step description "@is_fairstep(label='Add an awesome Watermark to your image (licence:cc0,author:rsiebes, date:06-05-2021 )') # Give it your own name: def my_watermark_step(image, text): from PIL import ImageFont from PIL import ImageDraw from PIL import Image watermark_image = image.copy() draw = ImageDraw.Draw(watermark_image) # add watermark draw.text((0, 0), text, (0, 0, 0)) # add watermark draw.text((0, 0), text, (255, 255, 255)) # new_image = .... return watermark_image " assertion.
- step description "@is_fairstep(label='Put here a name of your awesome step (include the word awesome so others will find it)') # Give it your own name: def my_awesome_step(image): from PIL import Image # new_image = .... return new_image " assertion.
- step description "@is_fairstep(label='AWESOME upside down flipper') # Give it your own name: def my_awesome_flipper(image): from PIL import Image new_image = image.rotate(180) return new_image " assertion.
- step description "@is_fairstep(label='add awesome filters') # Give it your own name: def add_awesome_filter(image_path): from PIL import Image, ImageFilter with Image.open(image_path) as im: new_image = im.filter(filter=ImageFilter.MinFilter) return new_image " assertion.
- step description "@is_fairstep(label='Add two numbers together') def add(a:float, b:float) -> float: return a + b " assertion.
- step description "@is_fairstep(label='Multiply two numbers together') def mul(a: float, b: float) -> float: return a * b " assertion.
- step description "@is_fairstep(label='Convert the image') def convert_image(img): from PIL import Image return img.convert('LA') " assertion.
- step description "@is_fairstep(label='contrast image by factor') def contrast_image(image, ratio): from PIL import Image, ImageEnhance new_image= image.convert('RGB') new_image = ImageEnhance.Contrast(image) new_image= new_image.enhance(ratio) return new_image " assertion.
- step description "@is_fairstep(label='Make white background of image transparent') def white_to_transparency(img): from PIL import Image img = img.convert("RGBA") data = img.getdata() new_data = [] for item in data: if item[0] == 255 and item[1] == 255 and item[2] == 255: new_data.append((255, 255, 255, 0)) else: new_data.append(item) img.putdata(new_data) return img " assertion.
- step description "@is_fairstep(label='Overlay image with another (partly transparent) one') def overlay(bg_img, fg_img): from PIL import Image img = bg_img.copy() fg_img = fg_img.convert("RGBA") img.paste(fg_img, (0, 0), fg_img) return img " assertion.
- step description "@is_fairstep(label='Put here a name of your awesome step (include the word awesome so others will find it)') # Give it your own name: def my_awesome_stepaww(image): from PIL import Image from PIL import Image, ImageFilter return image.filter(ImageFilter.BLUR) return new_image " assertion.
- step description "@is_fairstep(label='Convert image to grayscale') def rgb2gray_image(image): from PIL import Image new_image = image.convert('L') return new_image " assertion.
- step description "@is_fairstep(label='Add blur to image') def blur(img): from PIL import Image, ImageFilter return img.filter(ImageFilter.BLUR) " assertion.
- step description "@is_fairstep(label='contrast image by factor') def contrast_image(image, ratio): from PIL import Image, ImageEnhance new_image= image.convert('RGB') new_image = ImageEnhance.Contrast(image) new_image= new_image.enhance(ratio) return new_image " assertion.
- step description "@is_fairstep(label='Make white background of image transparent') def white_to_transparency(img): from PIL import Image img = img.convert("RGBA") data = img.getdata() new_data = [] for item in data: if item[0] == 255 and item[1] == 255 and item[2] == 255: new_data.append((255, 255, 255, 0)) else: new_data.append(item) img.putdata(new_data) return img " assertion.
- step description "@is_fairstep(label='Overlay image with another (partly transparent) one') def overlay(bg_img, fg_img): from PIL import Image img = bg_img.copy() fg_img = fg_img.convert("RGBA") img.paste(fg_img, (0, 0), fg_img) return img " assertion.
- plan description "@is_fairworkflow(label='awesome image maker') def awesome_image(image1, image2): transparent_image = white_to_transparency(image2) pixelated_image1 = my_awesome_adjustable_pixelization(image1, 0.4) new_image = overlay(pixelated_image1, transparent_image) return new_image " assertion.
- step description "@is_fairstep(label='awesome step to pixelize an image, with adjustable rate') # Give it your own name: def my_awesome_adjustable_pixelization(img, rate): newx = int(rate * img.size[0]) newy = int(rate * img.size[1]) imgSmall = img.resize((newx,newy),resample=Image.BILINEAR) result = imgSmall.resize(img.size,Image.NEAREST) return result " assertion.
- step description "@is_fairstep(label='awesome step to pixelize an image, with adjustable rate') # Give it your own name: def my_awesome_adjustable_pixelization(img, rate): newx = int(rate * img.size[0]) newy = int(rate * img.size[1]) imgSmall = img.resize((newx,newy),resample=Image.BILINEAR) result = imgSmall.resize(img.size,Image.NEAREST) return result " assertion.
- step description "@is_fairstep(label='Invert the grayscale image to get a negative') def inverter(gray_img): return 255-gray_img " assertion.
- step description "@is_fairstep(label='Blend and adjust the constrast of the final image') def dodge(front,back): result=front*255/(255-back) result[result>255]=255 result[back==255]=255 return result.astype('uint8') " assertion.
- plan description "@is_fairworkflow(label='workflow to convert an image to a pencil sketch') def mix_workflow(background, foreground): t3 = combine(background, foreground) t3.show return t3 " assertion.
- step description "@is_fairstep(label='An awesome step for creating composite image by blending images using a transparency mask') def mask_image(image1,image2): from PIL import Image mask = Image.new("L", image1.size, 128) new_image = Image.composite(image1, image2, mask) return new_image " assertion.
- step description "@is_fairstep(label='awesome smoothening of an image') # Give it your own name: def my_awesome_step(image): from PIL import Image # new_image = .... smoothenedImage = image.filter(ImageFilter.SMOOTH) new_image = image.filter(ImageFilter.SMOOTH_MORE) return new_image " assertion.
- step description "@is_fairstep(label='awesome smoothening of an image') # Give it your own name: def my_awesome_step(image): from PIL import Image # new_image = .... smoothenedImage = image.filter(ImageFilter.SMOOTH) new_image = image.filter(ImageFilter.SMOOTH_MORE) return new_image " assertion.
- plan description "@is_fairworkflow(label='My awesome workflow') def my_awesome_workflow(im_in, im_int): ## ... new_img = my_awesome_step(im_in) im_out = mask_image(new_img,im_int) return im_out " assertion.
- step description "@is_fairstep(label='awesome image converter') # Give it your own name: def awesome_image_converter(image): from PIL import Image, ImageEnhance new_image= image.convert('RGB') new_image = ImageEnhance.Contrast(image) new_image= new_image.enhance(0.5) new_image = Image.blend(image, new_image, alpha=0.9) return new_image " assertion.
- plan description "@is_fairworkflow(label='My awesome workflow') def my_awesome_workflow(im_in): im_out = awesome_image_converter(im_in) im_out = my_awesome_adjustable_pixelization(im_out, 0.2) return im_out " assertion.
- step description "@is_fairstep(label='Inverting the colors of an image') def invert_colors(img): from PIL import Image, ImageOps return ImageOps.invert(img) " assertion.
- step description "@is_fairstep(label='contrast image by factor') def contrast_image(image, ratio): from PIL import Image, ImageEnhance new_image= image.convert('RGB') new_image = ImageEnhance.Contrast(image) new_image= new_image.enhance(ratio) return new_image " assertion.
- plan description "@is_fairworkflow(label='A workflow converts an image to a pencil sketch') def image_to_pencil_sketch_workflow(origianl_image, ratio): gray_image = rgb2gray_image(origianl_image) inverted_image = invert_colors(gray_image) blurred_image = blur(inverted_image) blended_image = blend_image(gray_image, blurred_image) pencil_sketch_image = contrast_image(blended_image, ratio) return pencil_sketch_image " assertion.
- step description "@is_fairstep(label='Add blur to image') def blur(img): from PIL import Image, ImageFilter return img.filter(ImageFilter.BLUR) " assertion.
- step description "@is_fairstep(label='contrast image by factor') def contrast_image(image, ratio): from PIL import Image, ImageEnhance new_image= image.convert('RGB') new_image = ImageEnhance.Contrast(image) new_image= new_image.enhance(ratio) return new_image " assertion.
- step description "@is_fairstep(label='Add blur to image') def blur(img): from PIL import Image, ImageFilter return img.filter(ImageFilter.BLUR) " assertion.
- step description "@is_fairstep(label='Overlay image with another (partly transparent) one') def overlay(bg_img, fg_img): from PIL import Image img = bg_img.copy() fg_img = fg_img.convert("RGBA") img.paste(fg_img, (0, 0), fg_img) return img " assertion.
- step description "@is_fairstep(label='add awesome filters') # Give it your own name: def add_awesome_filter(image_path): from PIL import Image, ImageFilter with Image.open(image_path) as im: new_image = im.filter(filter=ImageFilter.MinFilter) return new_image " assertion.
- step description "@is_fairstep(label='Convert image to grayscale') def rgb2gray_image(image): from PIL import Image new_image = image.convert('L') return new_image " assertion.
- step description "@is_fairstep(label='Add blur to image') def blur(img): from PIL import Image, ImageFilter return img.filter(ImageFilter.BLUR) " assertion.
- step description "@is_fairstep(label='contrast image by factor') def contrast_image(image, ratio): from PIL import Image, ImageEnhance new_image= image.convert('RGB') new_image = ImageEnhance.Contrast(image) new_image= new_image.enhance(ratio) return new_image " assertion.
- step description "@is_fairstep(label='Adjust the constrast of the final image') def image_constrast(img:float, factor:float) -> float: enhancer = ImageEnhance.Contrast(img) img_constrast = enhancer.enhance(factor) return img_constrast " assertion.
- plan description "@is_fairworkflow(label='A simple image processing workflow, include grayscale, negative, guassian blur, blend, constrast') def image_combined_workflow(img1, img2): img_combined = image_combined(img1, img2) return img_combined " assertion.
- step description "@is_fairstep(label='Put here a name of your awesome step (include the word awesome so others will find it)') # Give it your own name: def xiao_func1(image:float) -> float: from PIL import Image, ImageDraw, ImageFont chars = "wow, what a beautiful image!" width, height = image.size chars_x, chars_y = int(width/8), int(height/3) ttf = ImageFont.load_default() img_draw = ImageDraw.Draw(image) img_draw.text((chars_x, chars_y), chars, font=ttf, fill=(255,0,0)) image.show() return img_draw " assertion.
- step description "@is_fairstep(label='Convert image to grayscale') def rgb2gray_image(image): from PIL import Image new_image = image.convert('L') return new_image " assertion.
- step description "@is_fairstep(label='Add blur to image') def blur(img): from PIL import Image, ImageFilter return img.filter(ImageFilter.BLUR) " assertion.
- step description "@is_fairstep(label='contrast image by factor') def contrast_image(image, ratio): from PIL import Image, ImageEnhance new_image= image.convert('RGB') new_image = ImageEnhance.Contrast(image) new_image= new_image.enhance(ratio) return new_image " assertion.
- step description "@is_fairstep(label='Add blur to image') def blur(img): from PIL import Image, ImageFilter return img.filter(ImageFilter.BLUR) " assertion.
- plan description "@is_fairworkflow(label='Combines two images together by overlapping them') def my_image_overlap_workflow(image1, image2): blurred_img = blur(image1) overlapped_image = blend_image(blurred_img, image2) return overlapped_image " assertion.
- step description "@is_fairstep(label='An awesome function to flip an image from left to right') def my_awesome_flipping(image): from PIL import Image # Flip the image from left to right image_flipped = image.transpose(method=Image.FLIP_LEFT_RIGHT) return image_flipped " assertion.
- step description "@is_fairstep(label='An awesome function to flip an image from left to right') def my_awesome_flipping(image): from PIL import Image # Flip the image from left to right image_flipped = image.transpose(method=Image.FLIP_LEFT_RIGHT) return image_flipped " assertion.
- plan description "@is_fairworkflow(label='My awesome workflow: flip left to right image and then write awesome text on it') def my_awesome_workflow(im_in): flipped_image = my_awesome_flipping(im_in) im_out = add_text_into_image(flipped_image) return im_out " assertion.
- step description "@is_fairstep(label='Convert image to grayscale') def rgb2gray_image(image): from PIL import Image new_image = image.convert('L') return new_image " assertion.
- step description "@is_fairstep(label='Blend two images') def blend_image(im1, im2): from PIL import Image im_blended= Image.blend(im1, im2, alpha=0.5) return im_blended " assertion.
- step description "@is_fairstep(label='contrast image by factor') def contrast_image(image, ratio): from PIL import Image, ImageEnhance new_image= image.convert('RGB') new_image = ImageEnhance.Contrast(image) new_image= new_image.enhance(ratio) return new_image " assertion.
- step description "@is_fairstep(label='Convert image to grayscale') def rgb2gray_image(image): from PIL import Image new_image = image.convert('L') return new_image " assertion.
- step description "@is_fairstep(label='Blend two images') def blend_image(im1, im2): from PIL import Image im_blended= Image.blend(im1, im2, alpha=0.5) return im_blended " assertion.
- plan description "@is_fairworkflow(label='An image to sketch conversion workflow') def my_workflow1(img1): img2 = rgb2gray_image(img1) img3 = invert_colors(img2) img4 = blur(img3) img5 = blend_image(img2,img4) img6 = contrast_image(img5,1) return img6 " assertion.
- step description "@is_fairstep(label='Overlay image with another (partly transparent) one') def overlay(bg_img, fg_img): from PIL import Image img = bg_img.copy() fg_img = fg_img.convert("RGBA") img.paste(fg_img, (0, 0), fg_img) return img " assertion.
- step description "@is_fairstep(label='Step to add text (awesome world!) into an image') # Give it your own name: def add_text_into_image(image): from PIL import ImageDraw from PIL import Image ImageDraw.Draw( image).text( (0, image.height/2), # Coordinates 'Awesome world!', # Text (255, 255, 255) # Color ) return image " assertion.
- step description "@is_fairstep(label='Convert image to grayscale') def rgb2gray_image(image): from PIL import Image new_image = image.convert('L') return new_image " assertion.
- step description "@is_fairstep(label='Add blur to image') def blur(img): from PIL import Image, ImageFilter return img.filter(ImageFilter.BLUR) " assertion.
- step description "@is_fairstep(label='contrast image by factor') def contrast_image(image, ratio): from PIL import Image, ImageEnhance new_image= image.convert('RGB') new_image = ImageEnhance.Contrast(image) new_image= new_image.enhance(ratio) return new_image " assertion.
- step description "@is_fairstep(label='Add blur to image') def blur(img): from PIL import Image, ImageFilter return img.filter(ImageFilter.BLUR) " assertion.
- plan description "@is_fairworkflow(label='Blend two images') def wf_t2(img1, img2): blurred_image = blur(img1) transparent_image = white_to_transparency(img2) new_image = overlay(blurred_image, transparent_image) return new_image " assertion.
- step description "@is_fairstep(label='Step to add text (awesome world!) into an image') # Give it your own name: def add_text_into_image(image): from PIL import ImageDraw from PIL import Image ImageDraw.Draw( image).text( (0, image.height/2), # Coordinates 'Awesome world!', # Text (255, 255, 255) # Color ) return image " assertion.
- step description "@is_fairstep(label='Inverting the colors of an image') def invert_colors(img): from PIL import Image, ImageOps return ImageOps.invert(img) " assertion.
- step description "@is_fairstep(label='An awesome step for creating composite image by blending images using a transparency mask') def mask_image(image1,image2): from PIL import Image mask = Image.new("L", image1.size, 128) new_image = Image.composite(image1, image2, mask) return new_image " assertion.
- step description "@is_fairstep(label='Add blur to image') def blur(img): from PIL import Image, ImageFilter return img.filter(ImageFilter.BLUR) " assertion.
- plan description "@is_fairworkflow(label='YAIB: Yet Another Image Blender (licence:cc0,author:rsiebes, date:06-05-2021 )') def yaib_workflow(backgroundImg,foregroundImg): blendedImg = mask_image(blur(backgroundImg),foregroundImg) return blendedImg " assertion.
- step description "@is_fairstep(label='Add an awesome Watermark to your image (licence:cc0,author:rsiebes, date:06-05-2021 )') # Give it your own name: def my_watermark_step(image, text): from PIL import ImageFont from PIL import ImageDraw from PIL import Image watermark_image = image.copy() draw = ImageDraw.Draw(watermark_image) # add watermark draw.text((0, 0), text, (0, 0, 0)) # add watermark draw.text((0, 0), text, (255, 255, 255)) # new_image = .... return watermark_image " assertion.
- step description "@is_fairstep(label='Inverting the colors of an image') def invert_colors(img): from PIL import Image, ImageOps return ImageOps.invert(img) " assertion.
- step description "@is_fairstep(label='Blend two images') def blend_image(im1, im2): from PIL import Image im_blended= Image.blend(im1, im2, alpha=0.5) return im_blended " assertion.
- step description "@is_fairstep(label='contrast image by factor') def contrast_image(image, ratio): from PIL import Image, ImageEnhance new_image= image.convert('RGB') new_image = ImageEnhance.Contrast(image) new_image= new_image.enhance(ratio) return new_image " assertion.
- step description "@is_fairstep(label='Make white background of image transparent') def white_to_transparency(img): from PIL import Image img = img.convert("RGBA") data = img.getdata() new_data = [] for item in data: if item[0] == 255 and item[1] == 255 and item[2] == 255: new_data.append((255, 255, 255, 0)) else: new_data.append(item) img.putdata(new_data) return img " assertion.
- step description "@is_fairstep(label='Add blur to image') def blur(img): from PIL import Image, ImageFilter return img.filter(ImageFilter.BLUR) " assertion.
- plan description "@is_fairworkflow(label='puts an image infront of a second image') def overlay_in_front(back_img, front_img): blur_back = blur(back_img) trans_front = white_to_transparency(front_img) final = overlay(blur_back, trans_front) return final " assertion.
- step description "@is_fairstep(label='awesome smoothening of an image') # Give it your own name: def my_awesome_step(image): from PIL import Image # new_image = .... smoothenedImage = image.filter(ImageFilter.SMOOTH) new_image = image.filter(ImageFilter.SMOOTH_MORE) return new_image " assertion.
- plan description "@is_fairworkflow(label='flip and smooth an image') def my_awesome_workflow(im_in): im_half = my_awesome_step(im_in) im_out = my_awesome_flipper(im_half) return im_out " assertion.
- step description "@is_fairstep(label='Convert the RGB color image to grayscale') def image_RGB2Gray(img:float) -> float: image_gray = img.convert('L') return image_gray " assertion.
- step description "@is_fairstep(label='Apply a Gaussian blur to the negative from step 2') def image_Gaussian(img:float) -> float: img_gauss = img.filter(ImageFilter.GaussianBlur(radius = 5)) return img_gauss " assertion.
- step description "@is_fairstep(label='Adjust the constrast of the final image') def image_constrast(img:float, factor:float) -> float: enhancer = ImageEnhance.Contrast(img) img_constrast = enhancer.enhance(factor) return img_constrast " assertion.
- usage-of-linked-data-scopes description "Usage of the Linked Data Scopes ontology in a research project" assertion.
- plan description "@is_fairworkflow(label='A simple image processing workflow, include grayscale, negative, guassian blur, blend, constrast') def image_combined_workflow(img1, img2): img_combined = image_combined(img1, img2) return img_combined " assertion.
- step description "@is_fairstep(label='An awesome step for creating composite image by blending images using a transparency mask') def mask_image(image1,image2): from PIL import Image mask = Image.new("L", image1.size, 128) new_image = Image.composite(image1, image2, mask) return new_image " assertion.
- RA1FoHM9lwJ1XAV1eB871XcMAKfod73G_i4YtgoLpJVH0 description "All review comments were addressed and responded to and the formalization looks good." assertion.
- RAXkuXJ4IK10Ai9F39_tOFDy6ewi7znau6OQhUEXP4nPc description "The author has addressed the review comments and the formalization looks good." assertion.
- RAokVMmiZSbRh01diNeJLum4p13kUd-NZjGFuVtxVz4Bs description "The review comments were addressed and the updated formalization looks good." assertion.
- RA22JAQihYeiJkNIjvwnxLPmjuG74yPcRXpPyVX8DV6fA description "All review comments were addressed and the formalization looks good." assertion.
- RAyg4UgIVovBGia-hk4qEuRzOq14fcOlYAclC6YGQaVYU description "The review comments were addressed and the updated formalization looks good." assertion.
- RAbWbJCYlLhlYBDn9PVxdJP_WUbbi058aRcK-3sOJsRwY description "All review comments were addressed and the formalization looks good." assertion.
- RAn15vsPJEVdJvjNKtBPo_oadtjeP9oc3Si-69FiJ4poQ description "The review comments were addressed and the formalization looks good." assertion.
- usage-of-linked-data-scopes description "Usage of the Linked Data Scopes ontology in a research project" assertion.
- RAoo8EvTgfkxJw5SgZXbJvRl5nQG7ygeGaHp8Zud1U4Zw description "The review comments were addressed and the formalization looks good." assertion.
- RABzhulhaPhOzo9MxWxl230N72-azdlpMNwu_HtDqsuUc description "The authors have responded to the review comments and the formalization looks good." assertion.
- IADOPT.MacromoleculeConcentration description "The concentration of macromolecules in the immune system in response to bacteria in the gut of a me/cfs patient" assertion.
- IADOPT.AirAldrinConcentration description "Mass concentration of Aldrin in air (passive sampler PUF, ng per sampler)" assertion.
- online-version-of-nanobench description "An online version of Nanobench would allow users to use it via the web without having to install it locally." assertion.
- www.wikidata.org description "Wikidata is a free and open knowledge base that can be read and edited by both humans and machines. Wikidata acts as central storage for the structured data of its Wikimedia sister projects including Wikipedia, Wikivoyage, Wiktionary, Wikisource, and others." assertion.
- lov.linkeddata.es description "LOV is the main catalog of vocabularies published and used on the Web. LOV provides a choice of several hundreds of such vocabularies, based on quality requirements including URI stability and availability on the Web, use of standard formats and publication best practices, quality metadata and documentation, identifiable and trustable publication body, proper versioning policy." assertion.