def hello_world(i):
templates = get_templates
strokeNumber = i
cs = strokes[i - 1]
strk = Stroke(x=cs['x'], y=cs['y'], t=cs['t'])
clean_segment_indices, segtypes = segment_stroke(strk)
best_match = classify_stroke(strk, templates)
return best_match
def normalize_segpoints(strokes):
"""
param stroke : a Stroke object with N x,y,t data points
return :
(template_x, template_y): a tuple of arrays representing the normalized X
and Y coordinates, ordered by time, of the points to be
used in the MHD calculation to compare against the given templates
Coordinates are normalized so that points span between 0 and 1
Relevant points would be the full set of stroke segment endpoints
and the curve segment midpoints
"""
#NORMALIZE THE STROKE POINTS
#GET THE SET OF POINTS TO BE USED IN THE MHD CALCULATION
template_x = []
template_y = []
for stroke in strokes:
segpoints, segtypes = segment_stroke(stroke)
assert len(segpoints) == len(segtypes) + 1
for i in range(len(segtypes)):
point = segpoints[i]
template_x.append(stroke.x[point])
template_y.append(stroke.y[point])
if segtypes[i] == 1:
midpoint = (segpoints[i] + segpoints[i + 1]) // 2
template_x.append(stroke.x[midpoint])
template_y.append(stroke.y[midpoint])
last_point = segpoints[-1]
template_x.append(stroke.x[last_point])
template_y.append(stroke.y[last_point])
num_arcs = sum([t for t in segtypes if t == 1])
# assert len(template_x) == len(segpoints) + num_arcs
min_x, max_x = min(template_x), max(template_x)
min_y, max_y = min(template_y), max(template_y)
diff_x = max_x - min_x
diff_y = max_y - min_y
template_x = [(x - min_x) / diff_x for x in template_x]
template_y = [(y - min_y) / diff_y for y in template_y]
print("\'x\':", template_x, ",")
print("\'y\':", template_y)
return template_x, template_y
def normalize_segpoints(stroke):
"""
param stroke : a Stroke object with N x,y,t data points
return :
(template_x, template_y): a tuple of arrays representing the normalized X
and Y coordinates, ordered by time, of the points to be
used in the MHD calculation to compare against the given templates
Coordinates are normalized so that points span between 0 and 1
Relevant points would be the full set of stroke segment endpoints
and the curve segment midpoints
"""
#NORMALIZE THE STROKE POINTS
segpoints, segtypes = segment_stroke(stroke)
#print("PTS", segpoints)
#print("TYPES", segtypes)
x = []
y = []
for j in range(len(segpoints)-1):
i = segpoints[j]
x.append(stroke.x[i])
y.append(stroke.y[i])
if segtypes[j] == 1:
start = i
end = segpoints[j+1]
mid = int((start+end)/2)
x.append(stroke.x[mid])
y.append(stroke.y[mid])
last = segpoints[-1]
x.append(stroke.x[last])
y.append(stroke.y[last])
max_x = max(x)
max_y = max(y)
min_x = min(x)
min_y = min(y)
x_norm = [(i-min_x)/(max_x-min_x) for i in x]
y_norm = [(i-min_y)/(max_y-min_y) for i in y]
#GET THE SET OF POINTS TO BE USED IN THE MHD CALCULATION
return (x_norm,y_norm)
9: "THREE FEATHERS",
10: "CHEF HAT",
11: "DOME",
12: "MUSIC NOTE"
}
if len(sys.argv) != 2:
raise ValueError('Error! Give stroke number after filename in command. \n e.g. python eval_stroke.py 2')
i = int(sys.argv[1])
if i <= len(strokes) and i > 0 or i == -1:
strokeNumber = i
cs = strokes[i-1]
strk = Stroke(x=cs['x'], y=cs['y'], t=cs['t'])
clean_segment_indices, segtypes = segment_stroke(strk)
best_match = classify_stroke(strk, templates)
print(f"{bcolors.BOLD}", "STROKE NUMBER:", strokeNumber, f"{bcolors.ENDC}")
print(f"{bcolors.BOLD}", "STROKE CLASS:", stroke_names[strokeNumber], f"{bcolors.ENDC}")
if best_match == stroke_names[strokeNumber]:
print(f"{bcolors.BOLD}", "YOUR CLASSIFICATION:", f"{bcolors.OKGREEN}", best_match, f"{bcolors.ENDC}", f"{bcolors.ENDC}")
else:
print(f"{bcolors.BOLD}", "YOUR CLASSIFICATION:", f"{bcolors.FAIL}", best_match, f"{bcolors.ENDC}", f"{bcolors.ENDC}")
plot_segmentation(strk, clean_segment_indices, segtypes)
plt.figure(1).canvas.set_window_title('MIT 6.835: Stroke Segmentation')
plt.show()
else:
msg = 'Stroke index out of range. Give a number between 1 and ' + str(strokes.size)
raise ValueError(msg)
