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- import cv2
- import Tool
- from scipy import ndimage
- class Denoise(Tool.Tool):
- def on_init(self):
- self.id = "denoise"
- self.name = "Denoise"
- self.icon_path = "ui/PF2_Icons/Denoise.png"
- self.properties = [
- # Detailer
- Tool.Property("enabled", "Denoise", "Header", False, has_toggle=True, has_button=False),
- Tool.Property("strength", "Strength", "Slider", 0, max=100, min=0),
- Tool.Property("w_strength", "White Strength", "Slider", 20, max=100, min=0),
- Tool.Property("b_strength", "Black Strength", "Slider", 70, max=100, min=0),
- Tool.Property("method", "Method", "Combo", 0, options=[
- "Mean",
- "Gaussian",
- ]),
- ]
- def on_update(self, image):
- im = image
- if(self.props["enabled"].get_value()):
- bpp = int(str(im.dtype).replace("uint", "").replace("float", ""))
- np = float(2 ** bpp - 1)
- method = self.props["method"].get_value()
- strength = self.props["strength"].get_value()
- b_strength = self.props["b_strength"].get_value()
- w_strength = self.props["w_strength"].get_value()
- filtered = None
- if(method == 0):
- filtered = ndimage.median_filter(im, 3)
- elif(method == 1):
- filtered = ndimage.gaussian_filter(im, 2)
- w_filter = im
- w_filter[im > (float(np) / 10) * 9] = filtered[im > (float(np) / 10) * 9]
- b_filter = im
- b_filter[im < (float(np) / 10)] = filtered[im < (float(np) / 10)]
- # Blend
- im = cv2.addWeighted(filtered, (strength / 100), im, 1 - (strength / 100), 0)
- im = cv2.addWeighted(w_filter, (w_strength / 100), im, 1 - (w_strength / 100), 0)
- im = cv2.addWeighted(b_filter, (b_strength / 100), im, 1 - (b_strength / 100), 0)
- return im
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