示例#1
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    def get_suggested_focal_point(self):
        with self.get_willow_image() as willow:
            faces = willow.detect_faces()

            if faces:
                # Create a bounding box around all faces
                left = min(face[0] for face in faces)
                top = min(face[1] for face in faces)
                right = max(face[2] for face in faces)
                bottom = max(face[3] for face in faces)
                focal_point = Rect(left, top, right, bottom)
            else:
                features = willow.detect_features()
                if features:
                    # Create a bounding box around all features
                    left = min(feature[0] for feature in features)
                    top = min(feature[1] for feature in features)
                    right = max(feature[0] for feature in features)
                    bottom = max(feature[1] for feature in features)
                    focal_point = Rect(left, top, right, bottom)
                else:
                    return None

        # Add 20% to width and height and give it a minimum size
        x, y = focal_point.centroid
        width, height = focal_point.size

        width *= 1.20
        height *= 1.20

        width = max(width, 100)
        height = max(height, 100)

        return Rect.from_point(x, y, width, height)
示例#2
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文件: models.py 项目: minusf/wagtail
 def get_focal_point(self):
     if (self.focal_point_x is not None and self.focal_point_y is not None
             and self.focal_point_width is not None
             and self.focal_point_height is not None):
         return Rect.from_point(
             self.focal_point_x,
             self.focal_point_y,
             self.focal_point_width,
             self.focal_point_height,
         )
示例#3
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 def get_focal_point(self):
     if self.focal_point_x is not None and \
        self.focal_point_y is not None and \
        self.focal_point_width is not None and \
        self.focal_point_height is not None:
         return Rect.from_point(
             self.focal_point_x,
             self.focal_point_y,
             self.focal_point_width,
             self.focal_point_height,
         )
示例#4
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文件: tests.py 项目: jams2/wagtail
 def test_from_point(self):
     rect = Rect.from_point(100, 200, 50, 20)
     self.assertEqual(rect, Rect(75, 190, 125, 210))
示例#5
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文件: tests.py 项目: sprymix/wagtail
 def test_from_point(self):
     rect = Rect.from_point(100, 200, 50, 20)
     self.assertEqual(rect, Rect(75, 190, 125, 210))
示例#6
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    def run(self, willow, image, env):
        image_width, image_height = willow.get_size()
        focal_point = image.get_focal_point()

        # Get crop aspect ratio
        crop_aspect_ratio = self.width / self.height

        # Get crop max
        crop_max_scale = min(image_width, image_height * crop_aspect_ratio)
        crop_max_width = crop_max_scale
        crop_max_height = crop_max_scale / crop_aspect_ratio

        # Initialise crop width and height to max
        crop_width = crop_max_width
        crop_height = crop_max_height

        # Use crop closeness to zoom in
        if focal_point is not None:
            # Get crop min
            crop_min_scale = max(focal_point.width,
                                 focal_point.height * crop_aspect_ratio)
            crop_min_width = crop_min_scale
            crop_min_height = crop_min_scale / crop_aspect_ratio

            # Sometimes, the focal point may be bigger than the image...
            if not crop_min_scale >= crop_max_scale:
                # Calculate max crop closeness to prevent upscaling
                max_crop_closeness = max(
                    1 - (self.width - crop_min_width) /
                    (crop_max_width - crop_min_width),
                    1 - (self.height - crop_min_height) /
                    (crop_max_height - crop_min_height))

                # Apply max crop closeness
                crop_closeness = min(self.crop_closeness, max_crop_closeness)

                if 1 >= crop_closeness >= 0:
                    # Get crop width and height
                    crop_width = crop_max_width + (
                        crop_min_width - crop_max_width) * crop_closeness
                    crop_height = crop_max_height + (
                        crop_min_height - crop_max_height) * crop_closeness

        # Find focal point UV
        if focal_point is not None:
            fp_x, fp_y = focal_point.centroid
        else:
            # Fall back to positioning in the centre
            fp_x = image_width / 2
            fp_y = image_height / 2

        fp_u = fp_x / image_width
        fp_v = fp_y / image_height

        # Position crop box based on focal point UV
        crop_x = fp_x - (fp_u - 0.5) * crop_width
        crop_y = fp_y - (fp_v - 0.5) * crop_height

        # Convert crop box into rect
        rect = Rect.from_point(crop_x, crop_y, crop_width, crop_height)

        # Make sure the entire focal point is in the crop box
        if focal_point is not None:
            rect = rect.move_to_cover(focal_point)

        # Don't allow the crop box to go over the image boundary
        rect = rect.move_to_clamp(Rect(0, 0, image_width, image_height))

        # Crop!
        willow = willow.crop(rect.round())

        # Get scale for resizing
        # The scale should be the same for both the horizontal and
        # vertical axes
        aftercrop_width, aftercrop_height = willow.get_size()
        scale = self.width / aftercrop_width

        # Only resize if the image is too big
        if scale < 1.0:
            # Resize!
            willow = willow.resize((self.width, self.height))

        return willow
    def run(self, willow, image, env):
        image_width, image_height = willow.get_size()
        focal_point = image.get_focal_point()

        # Get crop aspect ratio
        crop_aspect_ratio = self.width / self.height

        # Get crop max
        crop_max_scale = min(image_width, image_height * crop_aspect_ratio)
        crop_max_width = crop_max_scale
        crop_max_height = crop_max_scale / crop_aspect_ratio

        # Initialise crop width and height to max
        crop_width = crop_max_width
        crop_height = crop_max_height

        # Use crop closeness to zoom in
        if focal_point is not None:
            # Get crop min
            crop_min_scale = max(focal_point.width, focal_point.height * crop_aspect_ratio)
            crop_min_width = crop_min_scale
            crop_min_height = crop_min_scale / crop_aspect_ratio

            # Sometimes, the focal point may be bigger than the image...
            if not crop_min_scale >= crop_max_scale:
                # Calculate max crop closeness to prevent upscaling
                max_crop_closeness = max(
                    1 - (self.width - crop_min_width) / (crop_max_width - crop_min_width),
                    1 - (self.height - crop_min_height) / (crop_max_height - crop_min_height)
                )

                # Apply max crop closeness
                crop_closeness = min(self.crop_closeness, max_crop_closeness)

                if 1 >= crop_closeness >= 0:
                    # Get crop width and height
                    crop_width = crop_max_width + (crop_min_width - crop_max_width) * crop_closeness
                    crop_height = crop_max_height + (crop_min_height - crop_max_height) * crop_closeness

        # Find focal point UV
        if focal_point is not None:
            fp_x, fp_y = focal_point.centroid
        else:
            # Fall back to positioning in the centre
            fp_x = image_width / 2
            fp_y = image_height / 2

        fp_u = fp_x / image_width
        fp_v = fp_y / image_height

        # Position crop box based on focal point UV
        crop_x = fp_x - (fp_u - 0.5) * crop_width
        crop_y = fp_y - (fp_v - 0.5) * crop_height

        # Convert crop box into rect
        rect = Rect.from_point(crop_x, crop_y, crop_width, crop_height)

        # Make sure the entire focal point is in the crop box
        if focal_point is not None:
            rect = rect.move_to_cover(focal_point)

        # Don't allow the crop box to go over the image boundary
        rect = rect.move_to_clamp(Rect(0, 0, image_width, image_height))

        # Crop!
        willow = willow.crop(rect.round())

        # Get scale for resizing
        # The scale should be the same for both the horizontal and
        # vertical axes
        aftercrop_width, aftercrop_height = willow.get_size()
        scale = self.width / aftercrop_width

        # Only resize if the image is too big
        if scale < 1.0:
            # Resize!
            willow = willow.resize((self.width, self.height))

        return willow