reformat file with uniform indentation (d608926f) · Commits · github_fork / Stable Diffusion Webui

modules/textual_inversion/autocrop.py

+106 −104

Original line number	Diff line number	Diff line
		@@ -27,7 +27,6 @@ def crop_image(im, settings):
		elif is_portrait(settings.crop_width, settings.crop_height):
		scale_by = settings.crop_height / im.height


		im = im.resize((int(im.width * scale_by), int(im.height * scale_by)))
		im_debug = im.copy()

		@@ -71,6 +70,7 @@ def crop_image(im, settings):

		return results


		def focal_point(im, settings):
		corner_points = image_corner_points(im, settings) if settings.corner_points_weight > 0 else []
		entropy_points = image_entropy_points(im, settings) if settings.entropy_points_weight > 0 else []
		@@ -185,13 +185,15 @@ def image_face_points(im, settings):
		minsize = int(min(im.width, im.height) * t[1]) # at least N percent of the smallest side
		try:
		faces = classifier.detectMultiScale(gray, scaleFactor=1.1,
		minNeighbors=7, minSize=(minsize, minsize), flags=cv2.CASCADE_SCALE_IMAGE)
		minNeighbors=7, minSize=(minsize, minsize),
		flags=cv2.CASCADE_SCALE_IMAGE)
		except Exception:
		continue

		if faces:
		rects = [[f[0], f[1], f[0] + f[2], f[1] + f[3]] for f in faces]
		return [PointOfInterest((r[0] +r[2]) // 2, (r[1] + r[3]) // 2, size=abs(r[0]-r[2]), weight=1/len(rects)) for r in rects]
		return [PointOfInterest((r[0] + r[2]) // 2, (r[1] + r[3]) // 2, size=abs(r[0] - r[2]),
		weight=1 / len(rects)) for r in rects]
		return []