Svg conversions

.gitignore

@@ -158,3 +158,5 @@ cython_debug/
 #  and can be added to the global gitignore or merged into this file.  For a more nuclear
 #  option (not recommended) you can uncomment the following to ignore the entire idea folder.
 #.idea/
+/test/output
+/test/output

imagestamp.bat

@@ -0,0 +1 @@
+python %~dp0/src/main.py %*

src/classes/BlobDetector.py

@@ -0,0 +1,215 @@
+import cv2
+import numpy as np
+from PIL import Image
+import matplotlib.pyplot as plt
+import math
+
+class BlobDetector:
+
+    def __init__(self) -> None:
+
+        pass
+
+    def _get_contrast_points(self,_image_path)->list:
+        # read image
+        img = cv2.imread(_image_path)
+
+        # convert img to grayscale
+        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+
+        # do adaptive threshold on gray image
+        thresh = cv2.adaptiveThreshold(gray, 255, cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY, 101, 3)
+
+        # apply morphology open then close
+        kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5,5))
+        blob = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, kernel)
+        kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (9,9))
+        blob = cv2.morphologyEx(blob, cv2.MORPH_CLOSE, kernel)
+
+
+        cv2.imwrite("doco3_contour.jpg", blob)
+        cv2.imshow("IMAGE", blob)
+        cv2.waitKey(0)
+
+
+        image = Image.open("doco3_contour.jpg")
+
+    def _unsgined(self,_int:int)->int:
+        if _int < 0:
+            return _int*-1
+        return _int
+
+
+    def _square_color_variation_is_bellow_thres(self,_image:cv2.typing.MatLike,_top_x:int,_top_y:int,_width:int,_thres:int):
+        ...
+
+
+    def _pixels_color_variation_is_bellow_thres(self,_image:cv2.typing.MatLike,_pixels:list[list],_start_value:int=0,_thres:int=100)->bool:
+        last_value = _start_value
+        for pix in _pixels:
+            value = _image[pix["y"],pix["x"]] 
+            value_distance = self._unsgined(last_value -value )
+            if value_distance > _thres:
+                return False
+            last_value = value
+        return True
+
+
+    def _detect_contrast_points(self,_image_path:str,_width)->list:
+
+        image = cv2.imread(_image_path)
+
+        # grab the image dimensions
+        h = image.shape[0]
+        w = image.shape[1]
+
+        # convert img to grayscale
+        gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+
+        # do adaptive threshold on gray image
+        thresh = cv2.adaptiveThreshold(gray, 255, cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY, 101, 3)
+
+        #cv2.imshow("IMAGE", thresh)
+        #cv2.waitKey(0)
+
+        last_h_value = 0
+        thres = 200
+        points = []
+        aproximation = 1
+        last_x_value = 0
+        last_y_value = 0
+        x_distance = 0
+
+        max_points = 300
+
+        # loop over the image, pixel by pixel
+
+        padding = 5
+
+        final_with = _width+padding
+
+        for y in range(0, h):
+            if y % final_with != 0:
+                continue
+            for x in range(0, w):
+                if x % aproximation != 0:
+                    continue
+                value = thresh[y, x]
+                value_distance = self._unsgined(last_h_value -value )
+                last_h_value = value
+
+                '''
+                    distance_sum +=distance
+                    distance_count+=1
+
+                    average_distance = int(distance_sum/distance_count)
+                    print(average_distance)
+                '''
+                # does the gray value changed ? 
+                if value_distance > thres:
+                    # strat mesuring from this point
+                    last_x_value = x
+                    last_y_value = y
+
+                # mesure the distance where the gray  value of pixels are the same
+                x_distance = self._unsgined(last_x_value -x)
+                y_distance = self._unsgined(last_y_value -y)
+
+                # is there room for the qr code in this distance ? 
+                if x == 0:
+                    last_x_value = x
+                    last_y_value = y
+
+                if x_distance >= final_with :
+                    #does the qr code will be cut by the image border ? 
+                    if last_x_value+final_with > w:
+                        continue
+                    points.append({"x":last_x_value,"y":last_y_value})
+                    last_x_value = x
+                    last_y_value = y
+
+        return points
+
+
+    def _get_pixel_value(self,_image:Image,_x,_y):
+        im = Image.open('image.gif')
+        rgb_im = im.convert('RGB')
+        r, g, b = rgb_im.getpixel((_x, _y))
+        return r
+        print(r, g, b)
+        (65, 100, 137)
+
+
+    def get_blobs(self,_image_path:str,_min=200,_max=8000)->list:
+
+        return self._detect_contrast_points(_image_path,_min)
+
+        # read image
+        img = cv2.imread(_image_path)
+
+        # convert img to grayscale
+        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+
+        # do adaptive threshold on gray image
+        thresh = cv2.adaptiveThreshold(gray, 255, cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY, 101, 3)
+
+        # apply morphology open then close
+        kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5,5))
+        blob = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, kernel)
+        kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (9,9))
+        blob = cv2.morphologyEx(blob, cv2.MORPH_CLOSE, kernel)
+
+        # invert blob
+        blob = (255 - blob)
+
+        # Get contours
+        cnts = cv2.findContours(blob, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+        cnts = cnts[0] if len(cnts) == 2 else cnts[1]
+        #big_contour = max(cnts, key=cv2.contourArea)
+
+        filtered_contours = []
+        bounding_boxes = []
+
+        min = 100
+        max = 300000
+        for contour in cnts:
+            blob_area = cv2.contourArea(contour)
+            if blob_area < min:
+                continue
+            if blob_area > max:
+                continue
+            filtered_contours.append(contour)
+            rect = cv2.minAreaRect(contour)
+            box = cv2.boxPoints(rect)
+            box = np.int0(box)
+            bounding_boxes.append(box)
+            print(box)
+            ...
+
+        result = img.copy()
+
+        cv2.drawContours(result, filtered_contours, -1, (0,0,255), 1)
+        for box in bounding_boxes:
+            cv2.drawContours(result,[box],0,(0,255,0),2)
+
+        cv2.imwrite("doco3_contour.jpg", result)
+        cv2.imshow("RESULT", result)
+        cv2.waitKey(0)
+        return bounding_boxes
+
+        # test blob size
+        blob_area = cv2.contourArea(big_contour)
+        if blob_area < blob_area_thresh:
+            print("Blob Is Too Small")
+
+        # draw contour
+        result = img.copy()
+        cv2.drawContours(result, [big_contour], -1, (0,0,255), 1)
+
+        # write results to disk
+        cv2.imwrite("doco3_threshold.jpg", thresh)
+
+        # display it
+        return
+        cv2.imshow("IMAGE", img)
+        cv2.imshow("THRESHOLD", thresh)

src/classes/Combiner.py

@@ -0,0 +1,147 @@
+from PIL import Image
+import os
+import shutil
+import uuid
+from classes.ImageChecker import ImageChecker
+from classes.ImageEditor import ImageEditor
+
+class Combiner():
+
+    _IC = ImageChecker()
+    _IE:ImageEditor = ImageEditor()
+
+    def __init__(self):
+        self._axe= "H"
+        self._crop = True
+        ...
+
+    def combine(self,_paths:list)->str:
+        print(_paths)
+        images = _paths
+        if self._crop:
+            images = []
+            for path in _paths:
+                if self._IC.check(path)==None:
+                    return 
+                images.append(self._crop_to_bbox(path))
+        temp = self._generate_tmp_path()+".png"
+        if self._axe == "H":
+            self._combine_images_horizontaly(images,temp)
+        if self._axe == "V":
+            self._combine_images_verticaly(images,temp)
+        return temp
+
+    def set_axe(self,_axe:str):
+        self._axe = _axe
+        return self
+
+    def set_crop(self,_c:bool):
+        self._crop = _c
+        return self
+
+    def _combine_images_verticaly(self,_paths,_output,_padding=100):
+        for path in _paths:
+            if self._IC.check(path) is None:
+                return 
+        images = [Image.open(x) for x in _paths]
+        widths, heights = zip(*(i.size for i in images))
+
+        total_height = sum(heights)+(_padding*(len(_paths)+1))
+        max_width = max(widths)
+
+        new_im = Image.new('RGBA', (max_width,total_height))
+        path = self._IE.resize_by_width(self._IC.get_max_width())
+
+        x_offset = 0
+        y_offset = _padding
+
+        for im in images:
+            new_im.paste(im, (x_offset,y_offset))
+            x_offset += im.size[1]+_padding
+
+        new_im.save(_output)
+        return new_im
+
+    def _conform_images_width(self,_paths,_total_width)->list:
+        # check if the combined image is not too hudge (will cause errors on PIL side)
+        max_auhorised_width = self._IC.get_max_width()
+        conformed_paths = _paths
+        if _total_width >= max_auhorised_width:
+            print("[Combiner] WARNING ! final width is too high , resizing images ! ")
+            conformed_paths = []
+            forced_equal_width = int((max_auhorised_width/len(_paths))*0.95)
+            for path in _paths:
+                resized_image = self._IE.resize_by_width(path,forced_equal_width)
+                conformed_paths.append(resized_image)
+        return conformed_paths
+
+    def _combine_images_horizontaly(self,_paths,_output,_padding=100):
+        for path in _paths:
+            if self._IC.check(path)==None:
+                return 
+
+        # original width sum  and max heigth 
+        images = [Image.open(x) for x in _paths]
+        widths, heights = zip(*(i.size for i in images))
+        total_width = sum(widths)+(_padding*(len(_paths)+1))
+        max_height = max(heights)
+
+        #width check
+        conformed_paths = self._conform_images_width(_paths,total_width)
+        conformed_images = [Image.open(x) for x in conformed_paths]
+
+        # conformed width sum  and max heigth 
+        widths, heights = zip(*(i.size for i in conformed_images))
+        total_width = sum(widths)+(_padding*(len(_paths)+1))
+        max_height = max(heights)
+
+        new_im = Image.new('RGBA', (total_width, max_height))
+        max_height = max(heights)
+
+        x_offset =_padding
+        y_offset = 0
+
+        for im in conformed_images:
+            new_im.paste(im, (x_offset,y_offset))
+            x_offset += im.size[0]+_padding
+
+        new_im.save(_output)
+        return new_im
+
+    def _crop_to_bbox(self,_path:str)->str:
+
+        # Opens a image in RGB mode
+        im = Image.open(_path)
+        bbox = im.getbbox()
+
+        # Size of the image in pixels (size of original image)
+        # (This is not mandatory)
+        width, height = im.size
+
+        # Cropped image of above dimension
+        # (It will not change original image)
+        im1 = im.crop(bbox)
+
+        # Shows the image in image viewer
+        temp = self._generate_tmp_path()
+        ext = "."+_path.split(".")[-1]
+        im1.save(temp+ext)
+        return temp+ext
+
+    def _generate_tmp_path(self)->str:
+        image_folder= os.getenv("TEMP")
+        image_name = str(uuid.uuid4())[-15:]
+        path = image_folder+"/"+image_name
+        return path
+
+    def _copy_image_to_temp(self,_path):
+        image_temp = os.getenv("TEMP")
+        shutil.copy(_path, os.getenv("TEMP"))
+        return image_temp+"/"+os.path.basename(_path)        
+
+
+'''
+python P:/pipeline/dev/a.cormier/core/decorators/image_stamp/repos/ImageStamp/src/main.py -combine -i "P:/projects/billy/render/png/assets/library/master/ch_billy/t-0001.png" -i "P:/projects/billy/render/png/assets/library/master/ch_billy/t-0002.png" -o "P:/projects/riv/temp_no_backup/image_stamp"
+python P:/pipeline/dev/a.cormier/core/decorators/image_stamp/repos/ImageStamp/src/main.py -combine -i "P:/projects/billy/render/png/assets/library/master/ch_billy/t-0001.png" -i "P:/projects/billy/render/png/assets/library/master/ch_billy/t-0002.png" -i "P:/projects/billy/render/png/assets/library/master/ch_billy/t-0003.png" -o "P:/projects/riv/temp_no_backup/image_stamp"
+
+'''