def _preprocess_ability_icon(self, icon):
"""Preprocess an ability icon cut from frame.
Main idea here is to find color of icon first. Color of ability
icon is same as of arrow icon on right side. Given color, remove all parts
with different colors.
Author:
Appcell
Args:
None
Returns:
None
"""
ability_pos = OW.get_ability_icon_pos(self.player2['pos'])[self.game_type]
color = self.image_with_gap[ability_pos[
0] + ability_pos[1]/2, ability_pos[2] + ability_pos[3] + 6]
filtered_icon = np.zeros((icon.shape[0], icon.shape[1]))
# TODO: Labelling needed here!!! Especially when background looks
# similar to foreground.
# TODO: There must be a better way for this
for i in range(icon.shape[0]):
for j in range(icon.shape[1]):
if ImageUtils.color_distance(icon[i, j, :], color) \
< OW.ABILITY_ICON_COLOR_FILTER_THRESHOLD[self.game_type]:
filtered_icon[i, j] = 255
return filtered_icon.astype('uint8')
def get_headshot(self):
"""Tell if elimination comes with a headshot.
Author:
Appcell
Args:
None
Returns:
None
"""
ability_pos = OW.get_ability_icon_pos(self.player2['pos'])[self.game_type]
color = self.image_with_gap[ability_pos[
0] + ability_pos[1]/2, ability_pos[2] + ability_pos[3] + 6]
# TODO: Write consts here into ow.py
if ImageUtils.color_distance(color, np.array([255, 255, 255])) > 40:
self.is_headshot = True
def get_ability_and_assists(self):
"""Retrieve info of ability and assisting players in a row
If distance between 2 avatar icons, width of arrow icon removed, is
not divisible by width of an assist icon, then an ability icon must
exist somewhere. Cut it off and compare with all possible ability
icons to find the best match.
After removing ability icon & arrow icon, what's left between 2
avatars must be n assist icons. Cut each from killfeed image, and then
compare with references. Pick the one with maximum score as result.
All results are written into self.ability and self.assists.
Author:
Appcell
Args:
None
Returns:
None
"""
if self.player1['pos'] == -1 or self.player2['pos'] == -1:
return
distance = self.player2[
'pos'] - self.player1['pos'] - OW.KILLFEED_ICON_WIDTH[self.game_type]
gap = ImageUtils.crop(
self.image_with_gap,
[0, self.image_with_gap.shape[0], self.player1['pos'], distance])
ability_icon = ImageUtils.crop(
self.image_with_gap,
OW.get_ability_icon_pos(self.player2['pos'])[self.game_type])
# Error gets too much with lowQ videos. Use edge detection instead.
# Honestly it's not the best choice, since for non-OWL videos it
# doesn't work anymore. But again, for non-OWL videos we expect a
# better resolution.
edge_image = cv2.Canny(self.image, 100, 200)
# Get the "spanned" edge image.
roi_x_min = self.player1['pos'] + OW.KILLFEED_ICON_WIDTH[self.game_type] + 4
roi_x_max = self.player2['pos'] - OW.ABILITY_GAP_NORMAL[self.game_type]
if roi_x_max - roi_x_min < OW.ASSIST_GAP[self.game_type]:
return
edge_span = (np.sum(edge_image, 0) / 255)[roi_x_min:roi_x_max]
edges = list(filter(
lambda i: edge_span[i] >= self.image.shape[0] * 0.7,
range(0, roi_x_max - roi_x_min)))
if not edges:
# Assist avatar doesn't exist
return
edge = edges[-1] # The end of assist avatars list
assist_num = int(round(float(edge) / OW.ASSIST_GAP[self.game_type]))
ability_list = OW.ABILITY_LIST[self.player1['chara']]
ability_icons_ref = self.frame.game.ability_icons_ref[
self.player1['chara']]
if (distance - OW.ABILITY_GAP_NORMAL[self.game_type]) % OW.ASSIST_GAP[self.game_type] > 5:
# Has ability icon
max_prob = -10
for (ind, ability_index) in enumerate(ability_list):
filtered_icon = self._preprocess_ability_icon(ability_icon)
score = measure.compare_ssim(
filtered_icon,
ability_icons_ref[ind],
multichannel=True)
if score > max_prob:
max_prob = score
self.ability = ability_index
if max_prob < 0.1 and self.player1['chara'] == OW.GENJI:
self.ability = OW.ABILITY_E
for i in range(assist_num):
# TODO: write this into ow.py!
assist_icon = ImageUtils.crop(
self.image,
[
OW.ABILITY_ICON_Y_MIN[self.game_type],
OW.ASSIST_ICON_HEIGHT[self.game_type],
8 + self.player1['pos'] + i * OW.ASSIST_GAP[self.game_type] \
+ OW.KILLFEED_ICON_WIDTH[self.game_type],
OW.ASSIST_ICON_WIDTH[self.game_type]])
assist = {
"chara": "empty",
"player": "empty",
"team": self.player1['team']
}
max_score = -10
for (chara, icon) in self.frame.game.assist_icons_ref.iteritems():
score = measure.compare_ssim(assist_icon,
icon, multichannel=True)
if score > max_score:
max_score = score
assist['chara'] = chara
self.assists.append(self._set_assist_info(assist))