Matches in Nanopublications for { ?s <http://purl.org/dc/terms/description> ?o ?g. }
- step description "@is_fairstep(label='Subtract two numbers') def sub(a: float, b: float) -> float: return a - b " assertion.
- step description "@is_fairstep(label='A mathematical operation') def weird(a: float, b:float) -> float: return a * 2 + b * 4 " assertion.
- plan description "@is_fairworkflow(label='A simple addition, subtraction, multiplication workflow') def my_workflow(in1, in2, in3): t1 = add(in1, in2) t2 = sub(in1, in2) t3 = mul(weird(t1, in3), t2) return t3 " assertion.
- step description "@is_fairstep(label='Rotating an image represented by 90 degrees') def rotate_image(img): from PIL import Image return img.transpose(Image.ROTATE_90) " assertion.
- plan description "@is_fairworkflow(label='A simple addition, subtraction, multiplication workflow') def my_image_workflow(img1): img2 = rotate_image(img1) img3 = convert_image(img2) return img3 " 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='my workflow') def my_workflow1(img): im1 = rgb2gray_image(img) t2x = invert_colors(im1) im2= blur(t2x) t4x= blend_image(img,img) t5x=contrast_image(t4x,0.5) return t5x " assertion.
- plan description "@is_fairworkflow(label='my workflow') def my_workflow2(img1,img2): imgb=white_to_transparency(img2) imgc=overlay(imgb,img1) return imgc " 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.
- plan description "@is_fairworkflow(label='My awesome workflow') def my_awesome_workflow(im_in): im_out=my_awesome_stepaww(im_in) 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='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='A workflow to create a cool image') def convert_image(image): grayscale_image = rgb2gray_image(image) new_image = invert_colors(grayscale_image) new_image = blur(new_image) new_image = blend_image(new_image, grayscale_image) new_image = contrast_image(new_image, 5) 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 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.
- 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='Convert the RGB color image to grayscale') def grayscale(rgb): return np.dot(rgb[...,:3], [0.299, 0.587, 0.114]) " assertion.
- step description "@is_fairstep(label='Apply a Gaussian blur to the negative form') def blurrer(inverted_img): return scipy.ndimage.filters.gaussian_filter(inverted_img,sigma=5) " assertion.
- plan description "@is_fairworkflow(label='workflow to convert an image to a pencil sketch') def sketch_workflow(img): grey = grayscale(img) inv = inverter(grey) blur = blurrer(inv) t3 = dodge(blur, grey) return t3 " assertion.
- step description "@is_fairstep(label='Blend two images') def combine(background, foreground): return Image.blend(background, foreground, alpha=0.6) " 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.
- 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='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='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 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='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='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='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='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.
- 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='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.
- plan description "@is_fairworkflow(label='A workflow combine two images') def combine_images_workflow(bg_image, fg_image): blurred_image = blur(bg_image) transparent_image = white_to_transparency(fg_image) combined_image = overlay(blurred_image, transparent_image) return combined_image " assertion.
- plan description "@is_fairworkflow(label='My awesome filter workflow') def my_awesome_filter_workflow(image_path): result_image = add_awesome_filter(image_path) return result_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.
- plan description "@is_fairworkflow(label='Convert an image to pencil sketch workflow') def my_workflow1(image): t1 = rgb2gray_image(image) t2 = invert_colors(t1) t3 = blur(t2) t4 = blend_image(t1,t3) t5 = contrast_image(t4,0.) return t5 " 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='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="combine two pictures") def my_workflow2(image1,image2): t1 = blur(image1) t2 = contrast_image(image2,2) t3 = contrast_image(image1,0.5) t4 = blend_image(t3,t2) return t4 " assertion.
- step description "@is_fairstep(label='awesome picture') # Give it your own name: def awesome_picture(image): from PIL import Image new_image = image.convert('P') 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.
- plan description "@is_fairworkflow(label='My awesome workflow') def my_awesome_workflow(im_in): im_out1 = awesome_picture(im_in) im_out = my_awesome_adjustable_pixelization(im_out1, 0.4) ## ... 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='Invert the grayscale image to get a negative') def image_Gray2Negative(img:float) -> float: img_negative = PIL.ImageOps.invert(img) return img_negative " 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='Blend the grayscale image from step 1 with the blurred negative from step 3') def image_blend(img1:float, img2:float) -> float: img_blend = Image.blend(img1,img2,0.0) return img_blend " assertion.
- plan description "@is_fairworkflow(label='A simple image processing workflow, include grayscale, negative, guassian blur, blend, constrast') def image_processing_workflow(img): image_gray = image_RGB2Gray(img) image_negative = image_Gray2Negative(image_gray) img_gauss = image_Gaussian(image_negative) img_blend = image_blend(image_gray, img_gauss) img_constrast = image_constrast(img_blend, factor=0.3) return img_constrast " assertion.
- step description "@is_fairstep(label='Convert the RGB color image to grayscale') def image_combined(img1:float, img2:float) -> float: img_combined = Image.blend(img1, img2, 0.5) return img_combined " assertion.
- plan description "@is_fairworkflow(label='My awesome workflow') def xiao_workflow(im_in): im_out = xiao_func1(im_in) 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='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='A conversion from an image to a pencil sketch of that image') def my_image_conversion_workflow(inputImg): new_img_S1 = rgb2gray_image(inputImg) new_img_S2 = invert_colors(new_img_S1) new_img_S3 = blur(new_img_S2) new_img_S4 = blend_image(new_img_S1, new_img_S3) new_img_S5 = contrast_image(new_img_S4, 5) return new_img_S5 " 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='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='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='Add blur to image') def blur(img): from PIL import Image, ImageFilter return img.filter(ImageFilter.BLUR) " assertion.
- plan description "@is_fairworkflow(label='Example workflow') def my_workflow(img): gray = rgb2gray_image(img) neg = invert_colors(gray) gs = blur(neg) blend = blend_image(gray, gs) return contrast_image(blend, 1.5) " 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='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.
- plan description "@is_fairworkflow(label='An image overlaying workflow') def my_workflow2(img1, img2): img2t = white_to_transparency(img2) img3 = overlay(img1,img2t) return img3 " 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.
- plan description "@is_fairworkflow(label='My awesome workflow') def my_awesome_pixeltext_workflow(img_in): img1 = my_awesome_adjustable_pixelization(img_in,0.1) img_out = add_text_into_image(img1) return img_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='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='Convert an image to a pencil sketch') def wf_t1(image): gray_image = rgb2gray_image(image) negative_image = invert_colors(gray_image) blurred_image = blur(negative_image) blended_image = blend_image(gray_image, blurred_image) new_image = contrast_image(blended_image, 1) 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='Awesome step for rotating an image by any angle') # Give it your own name: def rotate_image(image, angle_rotation): new_image = image.rotate(angle=angle_rotation) return new_image " assertion.
- plan description "@is_fairworkflow(label='Awesome workflow for rotating and adding text to image') def wf_t3(im_in, angle): rotated_image = rotate_image(im_in, angle) im_out = add_text_into_image(rotated_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='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.
- plan description "@is_fairworkflow(label='YAIC: Yet Another Image Converter (licence:cc0,author:rsiebes,date:06-05-2021 )') def yaic_workflow(originalImg): grayImg = rgb2gray_image(originalImg) invertedImg = invert_colors(grayImg) blendedImg = mask_image(blur(invertedImg),originalImg) contrastedImg = contrast_image(blendedImg,2) return contrastedImg " 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='Make an image blurred and add copyright warning (licence:cc0,author:rsiebes, date:06-05-2021 )') def my_awesome_copyright_watermark_blur_workflow(im_in, text): blurredImg = blur(im_in) blurredWatermarkImg = my_watermark_step(blurredImg,text) return blurredWatermarkImg " 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.
- plan description "@is_fairworkflow(label='takes an images and returns a pencil sketch version') def to_pencil_sketch(original_image): gray = rgb2gray_image(original_image) neg_gray = invert_colors(gray) blur_neg_gray = blur(neg_gray) blended = blend_image(gray, blur_neg_gray) final = contrast_image(blended, 5) return final " 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='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='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='AWESOME upside down flipper') # Give it your own name: def my_awesome_flipper(image): from PIL import Image new_image = image.rotate(180) new_image.show() return new_image " assertion.
- step description "@is_fairstep(label='Invert the grayscale image to get a negative') def image_Gray2Negative(img:float) -> float: img_negative = PIL.ImageOps.invert(img) return img_negative " assertion.
- step description "@is_fairstep(label='Blend the grayscale image from step 1 with the blurred negative from step 3') def image_blend(img1:float, img2:float) -> float: img_blend = Image.blend(img1,img2,0.0) return img_blend " assertion.
- plan description "@is_fairworkflow(label='A simple image processing workflow, include grayscale, negative, guassian blur, blend, constrast') def image_processing_workflow(img): image_gray = image_RGB2Gray(img) image_negative = image_Gray2Negative(image_gray) img_gauss = image_Gaussian(image_negative) img_blend = image_blend(image_gray, img_gauss) img_constrast = image_constrast(img_blend, factor=0.3) return img_constrast " assertion.
- step description "@is_fairstep(label='Convert the RGB color image to grayscale') def image_combined(img1:float, img2:float) -> float: img_combined = Image.blend(img1, img2, 0.5) return img_combined " 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.
- RAmG2bXxwkIzARk4Mda-lqZU0RVnkpX7hUHBIPcdLHQUU description "All review comments were addressed and the formalization looks good." assertion.
- RAxBBJ2WkonyQNlXfdCAOaCi64J_xqgVGeaLjVQow9M88 description "The author has addressed all review comments received and the formalization looks good." assertion.
- RAeRSya2qIYymsBxiqOZP_oaQpHXUVXiydKvPCFM-7DDQ description "All review comments were addressed and the formalization looks good." assertion.