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Merge pull request #50 from PommeDroid/ultimate_refactoring_fix

Fix some regression for the no so ultimate refactor :D
tags/v1.2.10
deeppppp 2 years ago
parent
commit
8fead426b1
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+ 1
- 1
processing/folder.py View File

@@ -26,7 +26,7 @@ class FolderImageProcessing(MultipleImageProcessing):
self.__output_folder_path = self._args['output']
self.__multiprocessing = Conf.multiprocessing()

def _setup(self):
def _setup(self, *args):
Conf.log.debug([(r, d, f) for r, d, f in os.walk(self.__input_folder_path)])

for r, _, _ in os.walk(self.__input_folder_path):

+ 5
- 5
transform/opencv/bodypart/extract.py View File

@@ -84,9 +84,9 @@ def find_body_part(image, part_name):

xmax, xmin, ymax, ymin = BoundingBox.calculate_bounding_box(h, w, x, y)

bodypart_list.append(
BodyPart(part_name, BoundingBox(xmin, ymin, xmax, ymax), Center(x, y), Dimension(w, h))
)
BodyPart.add_body_part_to_list(part_name, BoundingBox(xmin, ymin, xmax, ymax), Center(x, y),
Dimension(w, h), bodypart_list)
return bodypart_list


@@ -131,10 +131,10 @@ def get_correct_filter_color(image, part_name):
color_mask = cv2.bitwise_or(color_mask1, color_mask2) # combine

elif part_name == "aur":
color_mask = get_simple_mask(image, [0, 0, 250], [0, 0, 250])
color_mask = get_simple_mask(image, [0, 0, 250], [0, 0, 255])

elif part_name == "vag":
color_mask = get_simple_mask(image, [250, 0, 0], [250, 0, 0])
color_mask = get_simple_mask(image, [250, 0, 0], [255, 0, 0])

elif part_name == "belly":
color_mask = get_simple_mask(image, [250, 0, 250], [255, 0, 255])

+ 5
- 8
transform/opencv/bodypart/inferrer.py View File

@@ -27,10 +27,8 @@ def infer_nip(aur_list):
# Calculate Bounding Box:
xmax, xmin, ymax, ymin = BoundingBox.calculate_bounding_box(nip_dim, nip_dim, x, y)

nip_list.append(
BodyPart("nip", BoundingBox(xmin, ymin, xmax, ymax), Center(x, y), Dimension(nip_dim, nip_dim)
)
)
BodyPart.add_body_part_to_list("nip", BoundingBox(xmin, ymin, xmax, ymax), Center(x, y),
Dimension(nip_dim, nip_dim), nip_list)

return nip_list

@@ -55,10 +53,9 @@ def infer_hair(vag_list, enable):
x = vag.x
y = vag.y - (hair_h / 2) - (vag.h / 2)

xmax, xmin, ymax, ymin = BoundingBox.calculate_bounding_box(hair_h,hair_w, x, y)
xmax, xmin, ymax, ymin = BoundingBox.calculate_bounding_box(hair_h, hair_w, x, y)

hair_list.append(
BodyPart("nip", BoundingBox(xmin, ymin, xmax, ymax), Center(x, y), Dimension(hair_w, hair_h))
)
BodyPart.add_body_part_to_list("hair", BoundingBox(xmin, ymin, xmax, ymax), Center(x, y),
Dimension(hair_w, hair_h), hair_list)

return hair_list

+ 10
- 11
transform/opencv/bodypart/resolver.py View File

@@ -90,10 +90,8 @@ def resolve_tit_aur_missing_problems(tits_list, aur_list, problem_code):
# Calculate Bounding Box:
xmax, xmin, ymax, ymin = BoundingBox.calculate_bounding_box(new_w, new_w, new_x, new_y)

tits_list.append(
BodyPart("tit", BoundingBox(xmin, ymin, xmax, ymax), Center(new_x, new_y),
Dimension(tits_list[0].w, tits_list[0].w))
)
BodyPart.add_body_part_to_list("tit", BoundingBox(xmin, ymin, xmax, ymax), Center(new_x, new_y),
Dimension(tits_list[0].w, tits_list[0].w), tits_list)

def resolve_problem_7():
# Add the first aur:
@@ -103,7 +101,8 @@ def resolve_tit_aur_missing_problems(tits_list, aur_list, problem_code):

xmax, xmin, ymax, ymin = BoundingBox.calculate_bounding_box(new_w, new_w, new_x, new_y)

BodyPart("aur", BoundingBox(xmin, ymin, xmax, ymax), Center(new_x, new_y), Dimension(new_w, new_w))
BodyPart.add_body_part_to_list("aur", BoundingBox(xmin, ymin, xmax, ymax), Center(new_x, new_y),
Dimension(new_w, new_w), aur_list)

# Add the second aur:
new_w = tits_list[1].w * random.uniform(0.03, 0.1) # TOTEST
@@ -128,12 +127,12 @@ def resolve_tit_aur_missing_problems(tits_list, aur_list, problem_code):
BodyPart.add_body_part_to_list("aur", BoundingBox(xmin, ymin, xmax, ymax), Center(new_x, new_y),
Dimension(aur_list[0].w, aur_list[0].w), aur_list)

{
3: resolve_problem_3,
6: resolve_problem_6,
7: resolve_problem_7,
8: resolve_problem_8,
}.get(problem_code, lambda: None)()
{
3: resolve_problem_3,
6: resolve_problem_6,
7: resolve_problem_7,
8: resolve_problem_8,
}.get(problem_code, lambda: None)()


def detect_tit_aur_position_problem(tits_list, aur_list):

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