Matches in Nanopublications for { ?s ?p "@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 " ?g. }
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- 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='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='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='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='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='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='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='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.