def run(img):
img = vision.convert_hsv_image_to_greyscale_emphasising_saturation(img)
ink = vision.binarize_ink_IMPROVED(img)
log.bgrOrGreyImage(ink)
skeleton = vision.skeletonize(ink)
log.bgrOrGreyImage(skeleton)
graph = topology.produce_graph(skeleton)
log.hsvOrGreyImage(img, pixels=graph.nodes())
log.gpickle(graph)
return graph
def run(graph, img):
graph = topology.simplify_junctures(graph)
log.hsvOrGreyImage(img,
points=(node for node in graph.nodes() if graph.degree(node) != 2)
)
graph = topology.simplify_paths(graph)
log.hsvOrGreyImage(img,
points=graph.nodes(),
lines=graph.edges()
)
graph = topology.hv_lines(graph)
log.hsvOrGreyImage(img,
points=graph.nodes(),
lines=graph.edges()
)
graph = satisfaction.align(graph)
log.hsvOrGreyImage(img,
points=graph.nodes(),
lines=graph.edges()
)
return graph
def run(img):
img = vision.convert_hsv_image_to_greyscale_emphasising_saturation(img)
ink = vision.binarize_ink_IMPROVED(img)
log.bgrOrGreyImage(ink)
skeleton = vision.skeletonize(ink)
log.bgrOrGreyImage(skeleton)
graph = topology.produce_graph(skeleton)
log.hsvOrGreyImage(img,
pixels=graph.nodes()
)
log.gpickle(graph)
return graph
def run(img):
img = extract_paper(img)
graph = sketch_graph(img)
graph = topology.simplify_junctures(graph)
log.hsvOrGreyImage(img, pixels=graph.nodes(), points=(node for node in graph.nodes() if graph.degree(node) != 2))
paths = topology.find_paths(graph)
corners = []
for path in paths:
corners.extend(corner_detection.find_corners(path))
log.hsvOrGreyImage(img, points=corners)
return graph
def run(img):
img = extract_paper(img)
graph = sketch_graph(img)
graph = topology.simplify_junctures(graph)
log.hsvOrGreyImage(img,
pixels=graph.nodes(),
points=(node for node in graph.nodes()
if graph.degree(node) != 2))
paths = topology.find_paths(graph)
corners = []
for path in paths:
corners.extend(corner_detection.find_corners(path))
log.hsvOrGreyImage(img, points=corners)
return graph
def run(img):
img = extract_paper(img)
graph = sketch_graph(img)
components = nx.connected_components(graph)
circles = [
topology.fit_circle_to_points(list(component))
for component in components
]
log.hsvOrGreyImage(img, circles=circles)
svg = printer.circles_to_svg(circles)
printer.write_file("log/out.svg", svg)
pdf = printer.svg_to_pdf("log/out.svg", "log/out.pdf")
printer.write_file("log/out.pdf", pdf)
# printer.print_pdf("log/out.pdf")
return graph
def run(img, logOn=True):
white_balanced_image = vision.white_balance(img)
hsv = cv2.cvtColor(white_balanced_image, cv2.COLOR_BGR2HSV)
if logOn: log.hsvOrGreyImage(hsv)
edges = vision.find_edges(hsv)
if logOn: log.hsvOrGreyImage(edges)
paper_contour = vision.find_paper(edges)
if logOn: log.hsvOrGreyImage(hsv, contours=[paper_contour])
extracted = vision.extract_paper(hsv, paper_contour)
if logOn: log.hsvOrGreyImage(extracted)
return extracted
def run(img, logOn=True):
white_balanced_image = vision.white_balance(img)
hsv = cv2.cvtColor(white_balanced_image, cv2.COLOR_BGR2HSV)
if logOn: log.hsvOrGreyImage(hsv)
edges = vision.find_edges(hsv)
if logOn: log.hsvOrGreyImage(edges)
paper_contour = vision.find_paper(edges)
if logOn: log.hsvOrGreyImage(hsv, contours=[paper_contour])
extracted = vision.extract_paper(hsv, paper_contour)
if logOn: log.hsvOrGreyImage(extracted)
return extracted
def run(img):
log.bgrOrGreyImage(img)
hsv = extract_paper(img, logOn=False)
log.hsvOrGreyImage(hsv)
grey = vision.convert_hsv_image_to_greyscale_emphasising_saturation(hsv)
binarized = vision.binarize_ink_IMPROVED(grey)
log.hsvOrGreyImage(binarized)
skeleton = vision.skeletonize(binarized)
log.hsvOrGreyImage(skeleton)
black = np.zeros((hsv.shape[0], hsv.shape[1], 3), dtype=np.uint8)
graph = topology.produce_graph(skeleton, hsv_image=hsv)
log.hsvOrGreyImage(black, pixels=graph.nodes(), graph=graph)
graph = topology.simplify_junctures(graph)
log.hsvOrGreyImage(
black,
pixels=graph.nodes(),
# lines=graph.edges(),
graph=graph,
)
mygraph, constraint_junctions = topology.find_same_length_constraints(graph)
log.hsvOrGreyImage(black, points=constraint_junctions, lines=mygraph.edges(), graph=mygraph)
graph = topology.simplify_paths(graph)
log.hsvOrGreyImage(black, points=graph.nodes(), lines=graph.edges())
graph = topology.hv_lines(graph)
log.hsvOrGreyImage(hsv, points=graph.nodes(), lines=graph.edges())
graph = satisfaction.align(graph)
log.hsvOrGreyImage(hsv, points=graph.nodes(), lines=graph.edges())
satisfaction.apply_same_length_constraint(graph)
def run(img):
log.bgrOrGreyImage(img)
hsv = extract_paper(img, logOn=False)
log.hsvOrGreyImage(hsv)
grey = vision.convert_hsv_image_to_greyscale_emphasising_saturation(hsv)
binarized = vision.binarize_ink_IMPROVED(grey)
log.hsvOrGreyImage(binarized)
skeleton = vision.skeletonize(binarized)
log.hsvOrGreyImage(skeleton)
black = np.zeros((hsv.shape[0], hsv.shape[1], 3), dtype=np.uint8)
graph = topology.produce_graph(skeleton, hsv_image=hsv)
log.hsvOrGreyImage(black,
pixels=graph.nodes(),
graph=graph
)
graph = topology.simplify_junctures(graph)
log.hsvOrGreyImage(black,
pixels=graph.nodes(),
# lines=graph.edges(),
graph=graph
)
mygraph, constraint_junctions = topology.find_same_length_constraints(graph)
log.hsvOrGreyImage(black,
points=constraint_junctions,
lines=mygraph.edges(),
graph=mygraph
)
graph = topology.simplify_paths(graph)
log.hsvOrGreyImage(black,
points=graph.nodes(),
lines=graph.edges()
)
graph = topology.hv_lines(graph)
log.hsvOrGreyImage(hsv,
points=graph.nodes(),
lines=graph.edges()
)
graph = satisfaction.align(graph)
log.hsvOrGreyImage(hsv,
points=graph.nodes(),
lines=graph.edges()
)
satisfaction.apply_same_length_constraint(graph)
