def save_parse_image_segments():
question = geoserver_interface.download_questions(1037).values()[0]
image_segment_parse = parse_image_segments(
open_image(question.diagram_path))
image = image_segment_parse.diagram_image_segment.segmented_image
file_path = "/Users/minjoon/Desktop/diagram.png"
cv2.imwrite(file_path, image)
def test_solving():
pk = 973
questions = geoserver_interface.download_questions(pk)
question = questions.values()[0]
label_data = geoserver_interface.download_labels(pk)[pk]
diagram = open_image(question.diagram_path)
graph_parse = diagram_to_graph_parse(diagram)
match_parse = parse_match_from_known_labels(graph_parse, label_data)
AB = v('AB', 'line')
AC = v('AC', 'line')
BC = v('BC', 'line')
ED = v('ED', 'line')
AE = v('AE', 'line')
E = v('E', 'point')
D = v('D', 'point')
x = v('x', 'number')
p1 = f('LengthOf', AB) == f('LengthOf', AC)
p2 = f('IsMidpointOf', E, AB)
p3 = f('IsMidpointOf', D, AC)
p4 = f('LengthOf', AE) == x
p5 = f('LengthOf', ED) == 4
qn = f('LengthOf', BC)
confident_atoms = parse_confident_formulas(graph_parse)
text_atoms = ground_formula_nodes(match_parse, [p1, p2, p3, p4, p5])
atoms = confident_atoms + text_atoms
grounded_qn = ground_formula_nodes(match_parse, [qn])[0]
ns = NumericSolver(atoms)
print ns.evaluate(grounded_qn)
def test_parse_graph():
questions = geoserver_interface.download_questions(973).values()
for question in questions:
image_segment_parse = parse_image_segments(
open_image(question.diagram_path))
primitive_parse = parse_primitives(image_segment_parse)
selected_primitive_parse = select_primitives(primitive_parse)
core_parse = parse_core(selected_primitive_parse)
graph_parse = parse_graph(core_parse)
print("Confident information in the diagram:")
for variable_node in parse_confident_atoms(graph_parse):
print variable_node
core_parse.display_points()
lines = get_all_instances(graph_parse, 'line')
circles = get_all_instances(graph_parse, 'circle')
arcs = get_all_instances(graph_parse, 'arc')
angles = get_all_instances(graph_parse, 'angle')
print("Displaying lines...")
for key, line in lines.iteritems():
graph_parse.display_instances([line])
print("Displaying circles...")
for key, circle in circles.iteritems():
graph_parse.display_instances([circle])
print("Displaying arcs...")
for key, arc in arcs.iteritems():
graph_parse.display_instances([arc])
print("Displaying angles...")
for key, angle in angles.iteritems():
graph_parse.display_instances([angle])
def test_parse_graph():
questions = geoserver_interface.download_questions(973).values()
for question in questions:
image_segment_parse = parse_image_segments(open_image(question.diagram_path))
primitive_parse = parse_primitives(image_segment_parse)
selected_primitive_parse = select_primitives(primitive_parse)
core_parse = parse_core(selected_primitive_parse)
graph_parse = parse_graph(core_parse)
print("Confident information in the diagram:")
for variable_node in parse_confident_atoms(graph_parse):
print variable_node
core_parse.display_points()
lines = get_all_instances(graph_parse, 'line')
circles = get_all_instances(graph_parse, 'circle')
arcs = get_all_instances(graph_parse, 'arc')
angles = get_all_instances(graph_parse, 'angle')
print("Displaying lines...")
for key, line in lines.iteritems():
graph_parse.display_instances([line])
print("Displaying circles...")
for key, circle in circles.iteritems():
graph_parse.display_instances([circle])
print("Displaying arcs...")
for key, arc in arcs.iteritems():
graph_parse.display_instances([arc])
print("Displaying angles...")
for key, angle in angles.iteritems():
graph_parse.display_instances([angle])
def test_ground_atoms():
pk = 973
questions = geoserver_interface.download_questions(pk)
question = questions.values()[0]
label_data = geoserver_interface.download_labels(pk)[pk]
diagram = open_image(question.diagram_path)
graph_parse = diagram_to_graph_parse(diagram)
match_parse = parse_match_from_known_labels(graph_parse, label_data)
AB = v('AB', 'line')
AC = v('AC', 'line')
BC = v('BC', 'line')
ED = v('ED', 'line')
AE = v('AE', 'line')
E = v('E', 'point')
D = v('D', 'point')
x = v('x', 'number')
p1 = f('LengthOf', AB) == f('LengthOf', AC)
p2 = f('IsMidpointOf', E, AB)
p3 = f('IsMidpointOf', D, AC)
p4 = f('LengthOf', AE) == x
p5 = f('LengthOf', ED) == 4
qn = f('LengthOf', BC)
grounded_atoms = ground_formula_nodes(match_parse,
[p1, p2, p3, p4, p5, qn])
for grounded_atom in grounded_atoms:
print grounded_atom
graph_parse.core_parse.display_points()
def test_solving():
pk = 973
questions = geoserver_interface.download_questions(pk)
question = questions.values()[0]
label_data = geoserver_interface.download_labels(pk)[pk]
diagram = open_image(question.diagram_path)
graph_parse = diagram_to_graph_parse(diagram)
match_parse = parse_match_from_known_labels(graph_parse, label_data)
AB = v('AB', 'line')
AC = v('AC', 'line')
BC = v('BC', 'line')
ED = v('ED', 'line')
AE = v('AE', 'line')
E = v('E', 'point')
D = v('D', 'point')
x = v('x', 'number')
p1 = f('LengthOf', AB) == f('LengthOf', AC)
p2 = f('IsMidpointOf', E, AB)
p3 = f('IsMidpointOf', D, AC)
p4 = f('LengthOf', AE) == x
p5 = f('LengthOf', ED) == 4
qn = f('LengthOf', BC)
confident_atoms = parse_confident_formulas(graph_parse)
text_atoms = ground_formula_nodes(match_parse, [p1, p2, p3, p4, p5])
atoms = confident_atoms + text_atoms
grounded_qn = ground_formula_nodes(match_parse, [qn])[0]
ns = NumericSolver(atoms)
print ns.evaluate(grounded_qn)
def test_ground_atoms():
pk = 973
questions = geoserver_interface.download_questions(pk)
question = questions.values()[0]
label_data = geoserver_interface.download_labels(pk)[pk]
diagram = open_image(question.diagram_path)
graph_parse = diagram_to_graph_parse(diagram)
match_parse = parse_match_from_known_labels(graph_parse, label_data)
AB = v('AB', 'line')
AC = v('AC', 'line')
BC = v('BC', 'line')
ED = v('ED', 'line')
AE = v('AE', 'line')
E = v('E', 'point')
D = v('D', 'point')
x = v('x', 'number')
p1 = f('LengthOf', AB) == f('LengthOf', AC)
p2 = f('IsMidpointOf', E, AB)
p3 = f('IsMidpointOf', D, AC)
p4 = f('LengthOf', AE) == x
p5 = f('LengthOf', ED) == 4
qn = f('LengthOf', BC)
grounded_atoms = ground_formula_nodes(match_parse, [p1, p2, p3, p4, p5, qn])
for grounded_atom in grounded_atoms:
print grounded_atom
graph_parse.core_parse.display_points()
def save_parse_primitives():
question = geoserver_interface.download_questions(1037).values()[0]
image_segment_parse = parse_image_segments(open_image(question.diagram_path))
primitive_parse = parse_primitives(image_segment_parse)
image = primitive_parse.get_image_primitives()
file_path = "/Users/minjoon/Desktop/primitives.png"
cv2.imwrite(file_path, image)
def question_to_graph_parse(question):
diagram = open_image(question.diagram_path)
image_segment_parse = parse_image_segments(diagram)
primitive_parse = parse_primitives(image_segment_parse)
selected_primitive_parse = select_primitives(primitive_parse)
core_parse = parse_core(selected_primitive_parse)
graph_parse = parse_graph(core_parse)
return graph_parse
def question_to_graph_parse(question):
diagram = open_image(question.diagram_path)
image_segment_parse = parse_image_segments(diagram)
primitive_parse = parse_primitives(image_segment_parse)
selected_primitive_parse = select_primitives(primitive_parse)
core_parse = parse_core(selected_primitive_parse)
graph_parse = parse_graph(core_parse)
return graph_parse
def save_parse_primitives():
question = geoserver_interface.download_questions(1037).values()[0]
image_segment_parse = parse_image_segments(
open_image(question.diagram_path))
primitive_parse = parse_primitives(image_segment_parse)
image = primitive_parse.get_image_primitives()
file_path = "/Users/minjoon/Desktop/primitives.png"
cv2.imwrite(file_path, image)
def test_select_primitives():
question_dict = geoserver_interface.download_questions('test')
for key in sorted(question_dict.keys()):
question = question_dict[key]
print(key)
image_segment_parse = parse_image_segments(open_image(question.diagram_path))
primitive_parse = parse_primitives(image_segment_parse)
selected = select_primitives(primitive_parse)
selected.display_primitives()
def test_parse_image_segments():
question = geoserver_interface.download_questions(1037).values()[0]
image_segment_parse = parse_image_segments(
open_image(question.diagram_path))
image_segment_parse.diagram_image_segment.display_binarized_segmented_image(
)
for idx, label_image_segment in image_segment_parse.label_image_segments.iteritems(
):
label_image_segment.display_segmented_image()
def _annotated_unit_test(query):
questions = geoserver_interface.download_questions(query)
all_annotations = geoserver_interface.download_semantics(query)
pk, question = questions.items()[0]
choice_formulas = get_choice_formulas(question)
label_data = geoserver_interface.download_labels(pk)[pk]
diagram = open_image(question.diagram_path)
graph_parse = diagram_to_graph_parse(diagram)
core_parse = graph_parse.core_parse
# core_parse.display_points()
# core_parse.primitive_parse.display_primitives()
match_parse = parse_match_from_known_labels(graph_parse, label_data)
match_formulas = parse_match_formulas(match_parse)
diagram_formulas = parse_confident_formulas(graph_parse)
all_formulas = match_formulas + diagram_formulas
for number, sentence_words in question.sentence_words.iteritems():
syntax_parse = stanford_parser.get_best_syntax_parse(sentence_words)
annotation_nodes = [annotation_to_semantic_tree(syntax_parse, annotation)
for annotation in all_annotations[pk][number].values()]
expr_formulas = {key: prefix_to_formula(expression_parser.parse_prefix(expression))
for key, expression in question.sentence_expressions[number].iteritems()}
truth_expr_formulas, value_expr_formulas = _separate_expr_formulas(expr_formulas)
text_formula_parse = semantic_trees_to_text_formula_parse(annotation_nodes)
completed_formulas = complete_formulas(text_formula_parse)
grounded_formulas = [ground_formula(match_parse, formula, value_expr_formulas)
for formula in completed_formulas+truth_expr_formulas]
text_formulas = filter_formulas(flatten_formulas(grounded_formulas))
all_formulas.extend(text_formulas)
reduced_formulas = reduce_formulas(all_formulas)
for reduced_formula in reduced_formulas:
score = evaluate(reduced_formula, core_parse.variable_assignment)
scores = [evaluate(child, core_parse.variable_assignment) for child in reduced_formula.children]
print reduced_formula, score, scores
# core_parse.display_points()
ans = solve(reduced_formulas, choice_formulas, assignment=core_parse.variable_assignment)
print "ans:", ans
if choice_formulas is None:
attempted = True
if abs(ans - float(question.answer)) < 0.01:
correct = True
else:
correct = False
else:
attempted = True
c = max(ans.iteritems(), key=lambda pair: pair[1].conf)[0]
if c == int(question.answer):
correct = True
else:
correct = False
result = SimpleResult(query, False, attempted, correct)
return result
def _annotated_unit_test(query):
questions = geoserver_interface.download_questions(query)
all_annotations = geoserver_interface.download_semantics(query)
pk, question = questions.items()[0]
choice_formulas = get_choice_formulas(question)
label_data = geoserver_interface.download_labels(pk)[pk]
diagram = open_image(question.diagram_path)
graph_parse = diagram_to_graph_parse(diagram)
core_parse = graph_parse.core_parse
# core_parse.display_points()
# core_parse.primitive_parse.display_primitives()
match_parse = parse_match_from_known_labels(graph_parse, label_data)
match_formulas = parse_match_formulas(match_parse)
diagram_formulas = parse_confident_formulas(graph_parse)
all_formulas = match_formulas + diagram_formulas
for number, sentence_words in question.sentence_words.iteritems():
syntax_parse = stanford_parser.get_best_syntax_parse(sentence_words)
annotation_nodes = [annotation_to_semantic_tree(syntax_parse, annotation)
for annotation in all_annotations[pk][number].values()]
expr_formulas = {key: prefix_to_formula(expression_parser.parse_prefix(expression))
for key, expression in question.sentence_expressions[number].iteritems()}
truth_expr_formulas, value_expr_formulas = _separate_expr_formulas(expr_formulas)
text_formula_parse = semantic_trees_to_text_formula_parse(annotation_nodes)
completed_formulas = complete_formulas(text_formula_parse)
grounded_formulas = [ground_formula(match_parse, formula, value_expr_formulas)
for formula in completed_formulas+truth_expr_formulas]
text_formulas = filter_formulas(flatten_formulas(grounded_formulas))
all_formulas.extend(text_formulas)
reduced_formulas = reduce_formulas(all_formulas)
for reduced_formula in reduced_formulas:
score = evaluate(reduced_formula, core_parse.variable_assignment)
scores = [evaluate(child, core_parse.variable_assignment) for child in reduced_formula.children]
print reduced_formula, score, scores
# core_parse.display_points()
ans = solve(reduced_formulas, choice_formulas, assignment=core_parse.variable_assignment)
print "ans:", ans
if choice_formulas is None:
attempted = True
if abs(ans - float(question.answer)) < 0.01:
correct = True
else:
correct = False
else:
attempted = True
c = max(ans.iteritems(), key=lambda pair: pair[1].conf)[0]
if c == int(question.answer):
correct = True
else:
correct = False
result = SimpleResult(query, False, attempted, correct)
return result
def test_select_primitives():
question_dict = geoserver_interface.download_questions('test')
for key in sorted(question_dict.keys()):
question = question_dict[key]
print(key)
image_segment_parse = parse_image_segments(
open_image(question.diagram_path))
primitive_parse = parse_primitives(image_segment_parse)
selected = select_primitives(primitive_parse)
selected.display_primitives()
def test_parse_match_from_known_labels():
questions = geoserver_interface.download_questions(977)
for pk, question in questions.iteritems():
label_data = geoserver_interface.download_labels(pk)[pk]
diagram = open_image(question.diagram_path)
graph_parse = diagram_to_graph_parse(diagram)
match_parse = parse_match_from_known_labels(graph_parse, label_data)
for key, value in match_parse.match_dict.iteritems():
print key, value
graph_parse.core_parse.display_points()
def test_parse_match_from_known_labels():
questions = geoserver_interface.download_questions(977)
for pk, question in questions.iteritems():
label_data = geoserver_interface.download_labels(pk)[pk]
diagram = open_image(question.diagram_path)
graph_parse = diagram_to_graph_parse(diagram)
match_parse = parse_match_from_known_labels(graph_parse, label_data)
for key, value in match_parse.match_dict.iteritems():
print key, value
graph_parse.core_parse.display_points()
def test_parse_match_atoms():
questions = geoserver_interface.download_questions(977)
for pk, question in questions.iteritems():
label_data = geoserver_interface.download_labels(pk)[pk]
diagram = open_image(question.diagram_path)
graph_parse = diagram_to_graph_parse(diagram)
match_parse = parse_match_from_known_labels(graph_parse, label_data)
match_atoms = parse_match_formulas(match_parse)
for match_atom in match_atoms:
print match_atom
graph_parse.core_parse.display_points()
def save_select_primitives():
question_dict = geoserver_interface.download_questions('test')
folder_path = "/Users/minjoon/Desktop/selected/"
for key in sorted(question_dict.keys()):
question = question_dict[key]
print(key)
image_segment_parse = parse_image_segments(open_image(question.diagram_path))
primitive_parse = parse_primitives(image_segment_parse)
selected = select_primitives(primitive_parse)
image = selected.get_image_primitives()
cv2.imwrite(os.path.join(folder_path, "%s.png" % str(question.key)), image)
def test_parse_match_atoms():
questions = geoserver_interface.download_questions(977)
for pk, question in questions.iteritems():
label_data = geoserver_interface.download_labels(pk)[pk]
diagram = open_image(question.diagram_path)
graph_parse = diagram_to_graph_parse(diagram)
match_parse = parse_match_from_known_labels(graph_parse, label_data)
match_atoms = parse_match_formulas(match_parse)
for match_atom in match_atoms:
print match_atom
graph_parse.core_parse.display_points()
def save_select_primitives():
question_dict = geoserver_interface.download_questions('test')
folder_path = "/Users/minjoon/Desktop/selected/"
for key in sorted(question_dict.keys()):
question = question_dict[key]
print(key)
image_segment_parse = parse_image_segments(
open_image(question.diagram_path))
primitive_parse = parse_primitives(image_segment_parse)
selected = select_primitives(primitive_parse)
image = selected.get_image_primitives()
cv2.imwrite(os.path.join(folder_path, "%s.png" % str(question.key)),
image)
def save_parse_core():
question_dict = geoserver_interface.download_questions('test')
folder_path = "/Users/minjoon/Desktop/core/"
for key in sorted(question_dict.keys()):
print(key)
question = question_dict[key]
file_path = os.path.join(folder_path, str(question.key) + ".png")
if os.path.isfile(file_path):
continue
image_segment_parse = parse_image_segments(open_image(question.diagram_path))
primitive_parse = parse_primitives(image_segment_parse)
selected = select_primitives(primitive_parse)
core_parse = parse_core(selected)
image = core_parse.get_image_points()
cv2.imwrite(file_path, image)
def save_parse_core():
question_dict = geoserver_interface.download_questions('test')
folder_path = "/Users/minjoon/Desktop/core/"
for key in sorted(question_dict.keys()):
print(key)
question = question_dict[key]
file_path = os.path.join(folder_path, str(question.key) + ".png")
if os.path.isfile(file_path):
continue
image_segment_parse = parse_image_segments(
open_image(question.diagram_path))
primitive_parse = parse_primitives(image_segment_parse)
selected = select_primitives(primitive_parse)
core_parse = parse_core(selected)
image = core_parse.get_image_points()
cv2.imwrite(file_path, image)
from geosolver.diagram.parse_image_segments import parse_image_segments
from geosolver.diagram.parse_primitives import parse_primitives
from geosolver.diagram.select_primitives import select_primitives
from geosolver.diagram.parse_core import parse_core
from geosolver.diagram.parse_graph import parse_graph
from geosolver.diagram.get_instances import get_all_instances
from geosolver.utils import prep
from geosolver.diagram.draw_on_image import *
import cv2
# demonstrate the image & parse image segments
image_path = 'tmp/all_images/8765.png'
image_segment_parse = parse_image_segments(prep.open_image(image_path))
# image_segment_parse.diagram_image_segment.display_segmented_image()
# prep.save_image(image_segment_parse.diagram_image_segment.segmented_image, 'tmp/t.png')
cv2.imwrite('tmp/results/source1.png', image_segment_parse.diagram_image_segment.segmented_image)
cv2.imwrite('tmp/results/sourceb.png', 255-image_segment_parse.diagram_image_segment.binarized_segmented_image)
# parse the primitive
primitive_parse = parse_primitives(image_segment_parse)
# primitive_parse.display_primitives()
cv2.imwrite('tmp/results/primitive1.png', primitive_parse.get_image_primitives())
# select the best set of primitive
selected = select_primitives(primitive_parse)
# selected.display_primitives()
cv2.imwrite('tmp/results/selected1.png', selected.get_image_primitives())
# point clustering
core_parse = parse_core(selected)
def test_parse_primitives():
question = geoserver_interface.download_questions(1037).values()[0]
image_segment_parse = parse_image_segments(open_image(question.diagram_path))
primitive_parse = parse_primitives(image_segment_parse)
primitive_parse.display_primitives()
def save_parse_image_segments():
question = geoserver_interface.download_questions(1037).values()[0]
image_segment_parse = parse_image_segments(open_image(question.diagram_path))
image = image_segment_parse.diagram_image_segment.segmented_image
file_path = "/Users/minjoon/Desktop/diagram.png"
cv2.imwrite(file_path, image)
def test_parse_image_segments():
question = geoserver_interface.download_questions(1037).values()[0]
image_segment_parse = parse_image_segments(open_image(question.diagram_path))
image_segment_parse.diagram_image_segment.display_binarized_segmented_image()
for idx, label_image_segment in image_segment_parse.label_image_segments.iteritems():
label_image_segment.display_segmented_image()
def test_parse_primitives():
question = geoserver_interface.download_questions(1037).values()[0]
image_segment_parse = parse_image_segments(
open_image(question.diagram_path))
primitive_parse = parse_primitives(image_segment_parse)
primitive_parse.display_primitives()
