def _test():
additional = [
# "/Users/danny/Dropbox (Dropbox)/Screenshots/Screenshot 2017-02-11 16.11.35.png",
# "/Users/danny/Dropbox (Dropbox)/Screenshots/Screenshot 2017-02-11 16.09.07.png",
"/Users/danny/Dropbox (Dropbox)/Screenshots/Screenshot 2017-02-11 16.28.04.png",
]
for path in list(ls(DATA_DIR + "module_classifier/labelled/simon_says", 1)) + additional:
im = cv2.imread(path)
if "/Screenshots/" in path:
from screenshot_helpers import MODULE_RECT
height = im.shape[0]
width = im.shape[1]
x1, x2, y1, y2 = MODULE_RECT
x1 = x1 * width / 100
x2 = x2 * width / 100
y1 = y1 * height / 100
y2 = y2 * height / 100
im = im[y1:y2, x1:x2]
offset = (0, 0)
color_to_position = get_square_positions(im, offset)
for color, position in color_to_position.items():
cv2.circle(im, position, 10, (255, 0, 0))
show(im)
def solve_stored_mazes():
vocab_path, unlabelled_dir, labelled_dir, features_dir, svm_data_dir = \
get_classifier_directories(MODULE_CLASSIFIER_DIR)
maze_dir = os.path.join(labelled_dir, "maze")
files_to_test = (
"/Users/danny/Dropbox (Personal)/Projects/KeepTalkingBot/module_specific_data/debug/0907.png",
)
for i, file_name in enumerate(os.listdir(maze_dir)):
# for file_name in files_to_test:
# if file_name != "0023-full-bottom-left.png":
# continue
print file_name
maze_image = cv2.imread(os.path.join(maze_dir, file_name))
lookup_key, start_coordinates, end_coordinates = get_maze_params(
maze_image)
print "lookup", lookup_key
print "start (white)", start_coordinates
print "end (red)", end_coordinates
top, right, bottom, left = get_button_locations(maze_image)
for location in (top, right, bottom, left):
cv2.circle(maze_image, location, 10, (255, 0, 0), 10)
show(maze_image)
# print top, right, bottom, left
moves = find_path_through_maze(lookup_key, start_coordinates,
end_coordinates)
print " ".join(moves)
def _test():
additional = [
# "/Users/danny/Dropbox (Dropbox)/Screenshots/Screenshot 2017-02-11 16.11.35.png",
# "/Users/danny/Dropbox (Dropbox)/Screenshots/Screenshot 2017-02-11 16.09.07.png",
"/Users/danny/Dropbox (Dropbox)/Screenshots/Screenshot 2017-02-11 16.28.04.png",
]
for path in list(ls(DATA_DIR + "module_classifier/labelled/simon_says",
1)) + additional:
im = cv2.imread(path)
if "/Screenshots/" in path:
from screenshot_helpers import MODULE_RECT
height = im.shape[0]
width = im.shape[1]
x1, x2, y1, y2 = MODULE_RECT
x1 = x1 * width / 100
x2 = x2 * width / 100
y1 = y1 * height / 100
y2 = y2 * height / 100
im = im[y1:y2, x1:x2]
offset = (0, 0)
color_to_position = get_square_positions(im, offset)
for color, position in color_to_position.items():
cv2.circle(im, position, 10, (255, 0, 0))
show(im)
def test():
# to_test = (275, 280)
# to_test = (1243, 1248)
to_test = (1331, 1336)
letter_classifier = inflate_classifier(PASSWORD_LETTER_CLASSIFIER_DIR)
for f in ls_debug(*to_test):
im = cv2.imread(f)
print get_letters(im, letter_classifier)
show(im)
def test():
to_test = (1254, 1255)
for path in ls_debug(*to_test):
print "---------- NEXT IMAGE ------------"
im = cv2.imread(path)
get_connections(im)
down_button = get_down_button(im)
cv2.circle(im, down_button, 20, (255, 0, 0), 20)
show(im)
def test():
to_test = (1254, 1255)
for path in ls_debug(*to_test):
print "---------- NEXT IMAGE ------------"
im = cv2.imread(path)
get_connections(im)
down_button = get_down_button(im)
cv2.circle(im, down_button, 20, (255, 0, 0), 20)
show(im)
def test():
# to_test = (275, 280)
# to_test = (1243, 1248)
to_test = (1331, 1336)
letter_classifier = inflate_classifier(PASSWORD_LETTER_CLASSIFIER_DIR)
for f in ls_debug(*to_test):
im = cv2.imread(f)
print get_letters(im, letter_classifier)
show(im)
def test():
images_to_test = (
"/Users/danny/Dropbox (Personal)/Projects/KeepTalkingBot/module_specific_data/debug/0530.png",
)
for f in images_to_test:
im = cv2.imread(f)
right_arrow = find_arrows(im)[1]
print right_arrow
cv2.circle(im, right_arrow, 10, (255, 0, 0), 10)
show(im)
def _test():
i = 0
for path in ls(DATA_DIR + "sides/batteries/raw_images"):
# if "-left.png" not in path:
# if "0030-edge-left.png" not in path:
# continue
i += 1
if i > 20:
break
# print path
im = cv2.imread(path)
from sides import _extract_side
im = _extract_side(im, "-bottom" in path)
print get_batteries_count_for_side(im)
show(im, .25)
def manually_group_images(classifier_dir):
vocab_path, unlabelled_dir, labelled_dir, features_dir, svm_data_dir = get_classifier_directories(classifier_dir)
for file_path in ls(unlabelled_dir):
folder_name = chr(show(cv2.imread(file_path)))
folder = os.path.join(labelled_dir, folder_name)
if not os.path.exists(folder):
os.makedirs(folder)
dst = os.path.join(labelled_dir, folder, os.path.basename(file_path))
shutil.copyfile(file_path, dst)
def test():
vocab_path, unlabelled_dir, labelled_dir, features_dir, svm_data_dir = \
get_classifier_directories(MODULE_CLASSIFIER_DIR)
for path in ls(os.path.join(labelled_dir, "password")):
im = cv2.imread(path)
letter_classifier = inflate_classifier(PASSWORD_LETTER_CLASSIFIER_DIR)
top_buttons, bottom_buttons = find_column_buttons(im)
submit_button = find_submit_button(im)
print get_letters(im, letter_classifier)
for i, b in enumerate(top_buttons):
cv2.circle(im, b, 5, (0, 0, 255))
cv2.putText(im, str(i), b, cv2.FONT_HERSHEY_PLAIN, 1, (0, 0, 0))
for i, b in enumerate(bottom_buttons):
cv2.circle(im, b, 5, (0, 255, 0))
cv2.putText(im, str(i), b, cv2.FONT_HERSHEY_PLAIN, 1, (0, 0, 0))
cv2.circle(im, submit_button, 5, (255, 0, 0))
show(im)
def test():
vocab_path, unlabelled_dir, labelled_dir, features_dir, svm_data_dir = \
get_classifier_directories(MODULE_CLASSIFIER_DIR)
for path in ls(os.path.join(labelled_dir, "password")):
im = cv2.imread(path)
letter_classifier = inflate_classifier(PASSWORD_LETTER_CLASSIFIER_DIR)
top_buttons, bottom_buttons = find_column_buttons(im)
submit_button = find_submit_button(im)
print get_letters(im, letter_classifier)
for i, b in enumerate(top_buttons):
cv2.circle(im, b, 5, (0, 0, 255))
cv2.putText(im, str(i), b, cv2.FONT_HERSHEY_PLAIN, 1, (0, 0, 0))
for i, b in enumerate(bottom_buttons):
cv2.circle(im, b, 5, (0, 255, 0))
cv2.putText(im, str(i), b, cv2.FONT_HERSHEY_PLAIN, 1, (0, 0, 0))
cv2.circle(im, submit_button, 5, (255, 0, 0))
show(im)
def manually_group_images(classifier_dir):
vocab_path, unlabelled_dir, labelled_dir, features_dir, svm_data_dir = get_classifier_directories(
classifier_dir)
for file_path in ls(unlabelled_dir):
folder_name = chr(show(cv2.imread(file_path)))
folder = os.path.join(labelled_dir, folder_name)
if not os.path.exists(folder):
os.makedirs(folder)
dst = os.path.join(labelled_dir, folder, os.path.basename(file_path))
shutil.copyfile(file_path, dst)
def _extract_pieces():
# _, _, labelled_src_dir, _, _ = get_classifier_directories(MODULE_CLASSIFIER_DIR)
# src_dir = os.path.join(labelled_src_dir, "memory")
# _, buttons_dir, _, _, _ = get_classifier_directories(BUTTONS_CLASSIFIER_DIR)
# _, screen_dir, _, _, _ = get_classifier_directories(SCREEN_CLASSIFIER_DIR)
# button_template = os.path.join(buttons_dir, "{:04}.png")
# screen_template = os.path.join(screen_dir, "{:04}.png")
#
# next_button = 0
# next_screen = 0
files = (
# "/Users/danny/Dropbox (Personal)/Projects/KeepTalkingBot/module_specific_data/debug/0121.png",
# "/Users/danny/Dropbox (Personal)/Projects/KeepTalkingBot/module_specific_data/debug/0122.png",
# "/Users/danny/Dropbox (Personal)/Projects/KeepTalkingBot/module_specific_data/debug/0123.png",
# "/Users/danny/Dropbox (Personal)/Projects/KeepTalkingBot/module_specific_data/debug/0135.png",
# "/Users/danny/Dropbox (Personal)/Projects/KeepTalkingBot/module_specific_data/debug/0973.png",
# "/Users/danny/Dropbox (Personal)/Projects/KeepTalkingBot/module_specific_data/debug/0974.png",
"/Users/danny/Dropbox (Personal)/Projects/KeepTalkingBot/module_specific_data/debug/0975.png",
# "/Users/danny/Dropbox (Personal)/Projects/KeepTalkingBot/module_specific_data/debug/0976.png",
# "/Users/danny/Dropbox (Personal)/Projects/KeepTalkingBot/module_specific_data/debug/0977.png",
# "/Users/danny/Dropbox (Personal)/Projects/KeepTalkingBot/module_specific_data/debug/0978.png",
)
button_classifier = inflate_classifier(BUTTONS_CLASSIFIER_DIR)
screen_classifier = inflate_classifier(SCREEN_CLASSIFIER_DIR)
for i, f in enumerate(files):
# if i >= 4:
# break
# if i != 3:
# continue
im = cv2.imread(f)
buttons = _get_button_images(im)
print _get_button_locations(im)
screen = _get_screen_image(im)
print "SCREEN:", screen_classifier(screen)
for b in buttons:
print "BUTTON:", button_classifier(b)
show(im)
def _extract_pieces():
# _, _, labelled_src_dir, _, _ = get_classifier_directories(MODULE_CLASSIFIER_DIR)
# src_dir = os.path.join(labelled_src_dir, "memory")
# _, buttons_dir, _, _, _ = get_classifier_directories(BUTTONS_CLASSIFIER_DIR)
# _, screen_dir, _, _, _ = get_classifier_directories(SCREEN_CLASSIFIER_DIR)
# button_template = os.path.join(buttons_dir, "{:04}.png")
# screen_template = os.path.join(screen_dir, "{:04}.png")
#
# next_button = 0
# next_screen = 0
files = (
# "/Users/danny/Dropbox (Personal)/Projects/KeepTalkingBot/module_specific_data/debug/0121.png",
# "/Users/danny/Dropbox (Personal)/Projects/KeepTalkingBot/module_specific_data/debug/0122.png",
# "/Users/danny/Dropbox (Personal)/Projects/KeepTalkingBot/module_specific_data/debug/0123.png",
# "/Users/danny/Dropbox (Personal)/Projects/KeepTalkingBot/module_specific_data/debug/0135.png",
# "/Users/danny/Dropbox (Personal)/Projects/KeepTalkingBot/module_specific_data/debug/0973.png",
# "/Users/danny/Dropbox (Personal)/Projects/KeepTalkingBot/module_specific_data/debug/0974.png",
"/Users/danny/Dropbox (Personal)/Projects/KeepTalkingBot/module_specific_data/debug/0975.png",
# "/Users/danny/Dropbox (Personal)/Projects/KeepTalkingBot/module_specific_data/debug/0976.png",
# "/Users/danny/Dropbox (Personal)/Projects/KeepTalkingBot/module_specific_data/debug/0977.png",
# "/Users/danny/Dropbox (Personal)/Projects/KeepTalkingBot/module_specific_data/debug/0978.png",
)
button_classifier = inflate_classifier(BUTTONS_CLASSIFIER_DIR)
screen_classifier = inflate_classifier(SCREEN_CLASSIFIER_DIR)
for i, f in enumerate(files):
# if i >= 4:
# break
# if i != 3:
# continue
im = cv2.imread(f)
buttons = _get_button_images(im)
print _get_button_locations(im)
screen = _get_screen_image(im)
print "SCREEN:", screen_classifier(screen)
for b in buttons:
print "BUTTON:", button_classifier(b)
show(im)
def _test():
for path in ls(DATA_DIR + "module_classifier/labelled/simple_wires", 5):
im = cv2.imread(path)
sides_info = SidesInfo(2, ["A", "B", "C", "D", "E", "2"])
positions, colors = get_wire_positions_and_colors(im)
index_to_cut = get_wire_index_to_cut(colors, sides_info)
color = colors[index_to_cut]
x, y = positions[index_to_cut]
radius = int(float(get_width(im) * 5) / 100.0)
circle_colors = {
WireColor.black: (0, 0, 0),
WireColor.white: (255, 255, 255),
WireColor.blue: (255, 0, 0),
WireColor.red: (0, 0, 255),
WireColor.yellow: (0, 255, 255),
}
cv2.circle(im, (x, y), radius, circle_colors[color])
show(im)
def sort_sides():
for path in ls(RAW_ORIG_SCREENSHOTS):
sequence_id = int(os.path.basename(path).split("-")[0])
if sequence_id <= 27 or sequence_id % 3 != 0:
continue
print path
im = cv2.imread(path)
height, width = im.shape[:2]
key = show(cv2.resize(im, (width / 4, height / 4)))
if key == ord("y"):
print "COPYING "
shutil.copy(path, os.path.join(EDGE_INDICATORS_SCREENSHOTS, os.path.basename(path)))
def _test():
vocab_path, unlabelled_dir, labelled_dir, features_dir, svm_data_dir = \
get_classifier_directories(SERIAL_IS_ZERO_CLASSIFIER_DIR)
letter_idx = 0
i = 0
group = 0
found_in_group = 0
# for path in ls(DATA_DIR + "module_classifier/unlabelled"):
for path in ls_debug(1294, 1297):
# if "-left.png" not in path:
# if "0036-edge-bottom.png" not in path:
# continue
# new_group = int(os.path.basename(path).split("-")[0])
# if new_group % 3 != 0:
# continue
# if new_group != group:
# if found_in_group != 1:
# "!!!! Found {} in group {} !!!!".format(found_in_group, group)
# found_in_group = 0
# group = new_group
i += 1
# if i == 1:
# continue
# if i > 1:
# break
print path
im = cv2.imread(path)
from sides import _extract_side
im = _extract_side(im, "-bottom" in path)
text = get_serial_number_from_side(im)
if text is None:
print "NO SERIAL NUMBER"
else:
print "-".join(text)
text_threshold = _get_cleaned_up_text_subsection(im)
if text_threshold is not None:
show(text_threshold)
def _test():
vocab_path, unlabelled_dir, labelled_dir, features_dir, svm_data_dir = \
get_classifier_directories(SERIAL_IS_ZERO_CLASSIFIER_DIR)
letter_idx = 0
i = 0
group = 0
found_in_group = 0
# for path in ls(DATA_DIR + "module_classifier/unlabelled"):
for path in ls_debug(1294, 1297):
# if "-left.png" not in path:
# if "0036-edge-bottom.png" not in path:
# continue
# new_group = int(os.path.basename(path).split("-")[0])
# if new_group % 3 != 0:
# continue
# if new_group != group:
# if found_in_group != 1:
# "!!!! Found {} in group {} !!!!".format(found_in_group, group)
# found_in_group = 0
# group = new_group
i += 1
# if i == 1:
# continue
# if i > 1:
# break
print path
im = cv2.imread(path)
from sides import _extract_side
im = _extract_side(im, "-bottom" in path)
text = get_serial_number_from_side(im)
if text is None:
print "NO SERIAL NUMBER"
else:
print "-".join(text)
text_threshold = _get_cleaned_up_text_subsection(im)
if text_threshold is not None:
show(text_threshold)
def sort_sides():
for path in ls(RAW_ORIG_SCREENSHOTS):
sequence_id = int(os.path.basename(path).split("-")[0])
if sequence_id <= 27 or sequence_id % 3 != 0:
continue
print path
im = cv2.imread(path)
height, width = im.shape[:2]
key = show(cv2.resize(im, (width / 4, height / 4)))
if key == ord("y"):
print "COPYING "
shutil.copy(
path,
os.path.join(EDGE_INDICATORS_SCREENSHOTS,
os.path.basename(path)))