167 lines
5.4 KiB
Python
167 lines
5.4 KiB
Python
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#!/usr/bin/env python3
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# Copyright (C) 2022 Samir OUCHENE, samirmath01@gmail.com
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import os
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import sys
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import io
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import inkex
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from inkex import Image
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from PIL import Image as PIL_Image
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import base64
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import numpy
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try:
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from base64 import decodebytes
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except ImportError:
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from base64 import decodestring as decodebytes
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class RasterPerspective(inkex.Effect):
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def __init__(self):
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inkex.Effect.__init__(self)
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@staticmethod
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def mime_to_ext(mime):
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"""Return an extension based on the mime type"""
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# Most extensions are automatic (i.e. extension is same as minor part of mime type)
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part = mime.split("/", 1)[1].split("+")[0]
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return (
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"."
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+ {
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# These are the non-matching ones.
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"svg+xml": ".svg",
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"jpeg": ".jpg",
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"icon": ".ico",
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}.get(part, part)
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)
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def extract_image(self, node):
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"""Extract the node as if it were an image."""
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xlink = node.get("xlink:href")
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if not xlink.startswith("data:"):
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return # Not embedded image data
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try:
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data = xlink[5:]
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(mimetype, data) = data.split(";", 1)
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(base, data) = data.split(",", 1)
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except ValueError:
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inkex.errormsg("Invalid image format found")
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return
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if base != "base64":
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inkex.errormsg("Can't decode encoding: {}".format(base))
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return
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file_ext = self.mime_to_ext(mimetype)
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return decodebytes(data.encode("utf-8"))
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def find_coeffs(self, source_coords, target_coords):
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matrix = []
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for s, t in zip(source_coords, target_coords):
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matrix.append([t[0], t[1], 1, 0, 0, 0, -s[0] * t[0], -s[0] * t[1]])
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matrix.append([0, 0, 0, t[0], t[1], 1, -s[1] * t[0], -s[1] * t[1]])
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A = numpy.array(matrix, dtype=float)
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B = numpy.array(source_coords).reshape(8)
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res = numpy.linalg.inv(A.T @ A) @ A.T @ B
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return numpy.array(res).reshape(8)
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def effect(self):
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the_image_node, envelope_node = self.svg.selection
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if str(envelope_node) == "image" and str(the_image_node) == "path":
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envelope_node, the_image_node = self.svg.selection #switch
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if str(the_image_node) != "image" and str(envelope_node) != "path":
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inkex.utils.debug("Your selection must contain an image and a path with at least 4 points.")
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return
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img_width, img_height = the_image_node.width, the_image_node.height
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try:
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unit_to_vp = self.svg.unit_to_viewport
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except AttributeError:
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unit_to_vp = self.svg.uutounit
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try:
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vp_to_unit = self.svg.viewport_to_unit
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except AttributeError:
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vp_to_unit = self.svg.unittouu
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img_width = unit_to_vp(img_width)
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img_height = unit_to_vp(img_height)
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nodes_pts = list(envelope_node.path.control_points)
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node1 = (unit_to_vp(nodes_pts[0][0]), unit_to_vp(nodes_pts[0][1]))
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node2 = (unit_to_vp(nodes_pts[1][0]), unit_to_vp(nodes_pts[1][1]))
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node3 = (unit_to_vp(nodes_pts[2][0]), unit_to_vp(nodes_pts[2][1]))
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node4 = (unit_to_vp(nodes_pts[3][0]), unit_to_vp(nodes_pts[3][1]))
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nodes = [node1, node2, node3, node4]
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xMax = max([node[0] for node in nodes])
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xMin = min([node[0] for node in nodes])
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yMax = max([node[1] for node in nodes])
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yMin = min([node[1] for node in nodes])
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# add some assertions (FIXME)
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img_data = self.extract_image(the_image_node)
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orig_image = PIL_Image.open(io.BytesIO(img_data))
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pil_img_size = orig_image.size
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scale = pil_img_size[0] / img_width
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coeffs = self.find_coeffs(
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[
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(0, 0),
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(img_width * scale, 0),
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(img_width * scale, img_height * scale),
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(0, img_height * scale),
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],
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[
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(node1[0] - xMin, node1[1] - yMin),
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(node2[0] - xMin, node2[1] - yMin),
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(node3[0] - xMin, node3[1] - yMin),
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(node4[0] - xMin, node4[1] - yMin),
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],
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)
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W, H = xMax - xMin, yMax - yMin
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final_w, final_h = int(W), int(H)
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# Check if the image has transparency
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hasTransparency = orig_image.mode in ("RGBA", "LA") or (
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orig_image.mode == "P" and "transparency" in orig_image.info
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)
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transp_img = orig_image
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# If the original image is not transparent, create a new image with alpha channel
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if not hasTransparency:
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transp_img = PIL_Image.new("RGBA", orig_image.size)
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transp_img.format = "PNG"
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transp_img.paste(orig_image)
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image = transp_img.transform(
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(final_w, final_h), PIL_Image.PERSPECTIVE, coeffs, PIL_Image.BICUBIC
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)
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obj = inkex.Image()
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obj.set("x", vp_to_unit(xMin))
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obj.set("y", vp_to_unit(yMin))
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obj.set("width", vp_to_unit(final_w))
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obj.set("height", vp_to_unit(final_h))
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# embed the transformed image
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persp_img_data = io.BytesIO()
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image.save(persp_img_data, transp_img.format)
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mime = PIL_Image.MIME[transp_img.format]
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b64 = base64.b64encode(persp_img_data.getvalue()).decode("utf-8")
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uri = f"data:{mime};base64,{b64}"
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obj.set("xlink:href", uri)
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self.svg.add(obj)
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RasterPerspective = RasterPerspective()
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RasterPerspective.run()
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