Matches in Nanopublications for { ?s <http://purl.org/dc/terms/description> ?o ?g. }
- 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.
- RAyE_qJYzZXoMcHEY3z_x5qgpWWCdjWi6dpNr4UWFWzwo description "accepted as is" assertion.
- assertion description "Such a nanopublication includes a text that refers to an existing paper or other document, such as stating an agreement or a correction. The reference to the existing paper is based on the <a href="https://sparontologies.github.io/cito/current/cito.html" target="_blank">Citation Typing Ontology (CiTO)</a>." assertion.
- assertion description "Such a nanopublication represents an annotation of a text according to the <a href="https://www.w3.org/ns/oa">Web Annotation Vocabulary</a>." assertion.
- assertion description "This template allows you to make annotate external resources (e.g., papers, software, published datasets) with their RDF stream type, according to RDF-STaX. The assertion is subjective and it includes information on who made it (you) and how was it derived from the source material. More information about RDF-STaX: https://w3id.org/stax" assertion.
- assertion description "This template allows you to make annotate external resources (e.g., papers, software, published datasets) with their RDF stream type, according to RDF-STaX. The assertion is subjective and it includes information on who made it (you) and how was it derived from the source material. More information about RDF-STaX: https://w3id.org/stax" assertion.
- assertion description "This template allows you to make annotate external resources (e.g., papers, software, published datasets) with their RDF stream type, according to RDF-STaX. The assertion is subjective and it includes information on who made it (you) and how was it derived from the source material. More information about RDF-STaX: https://w3id.org/stax" assertion.
- assertion description "This template allows you to make annotate external resources (e.g., papers, software, published datasets) with their RDF stream type, according to RDF-STaX. The assertion is subjective and it includes information on who made it (you) and how was it derived from the source material. More information about RDF-STaX: https://w3id.org/stax" assertion.
- assertion description "This template allows you to make annotate external resources (e.g., papers, software, published datasets) with their RDF stream type, according to RDF-STaX. The assertion is subjective and it includes information on who made it (you) and how was it derived from the source material. More information about RDF-STaX: https://w3id.org/stax" assertion.
- assertion description "Template for defining a community of practice aiming at implementing the FAIR principles." assertion.
- assertion description "Such a nanopublication contains the main high-level metadata about a scholarly article, including title, authors, and links to other nanopublications." assertion.
- assertion description "Template for defining a provenance model." assertion.
- assertion description "Template for defining a community of practice aiming at implementing the FAIR principles." assertion.
- assertion description "Template for defining a provenance model." assertion.
- research-activity description document provenance.
- research-activity description document provenance.
- research-activity description document provenance.
- research-activity description document provenance.
- research-activity description document provenance.
- research-activity description document provenance.
- fip description "GEOROC | Geochemistry of Rocks of the Oceans and Continents)" assertion.
- fip description "COVID-19 INSPIRE Population Health FIP" assertion.
- research-activity description document provenance.
- test description "just testing..." assertion.
- research-activity description document provenance.
- research-activity description document provenance.
- research-activity description 20800271 provenance.
- fip description "NanoPharos | NanoPharos Database: Ready-for-Modelling Datasets for Nanoinformatics: NanoPharos Database: Ready-for-Modelling Datasets for Nanoinformatics" assertion.
- research-activity description document provenance.
- test description "this is a test" assertion.
- research-activity description document provenance.
- fip description "" assertion.
- fip description "This is the FIP for the IAGOS Community representing the choices made in 2019." assertion.
- fip description "IAGOS FIP 2019: This is the FIP for the IAGOS Community representing the choices made in 2019." assertion.