import cv2 import numpy as np import typing import pointcluster from shapes import Rect from utility import * class CVImage: """Dummy definition to allow recursive type hints""" pass class CVImage: def __init__(self, label="", img:np.ndarray=None, **kwargs): """You can provide a 'filename' keyword arg to automatically load a file.""" self.label = label self.image = img self._init_kwargs = kwargs if kwargs: load_kwargs = dict(kwargs) # copy self.load(**load_kwargs) @property def is_color(self): return len(self.image.shape) == 3 def load(self, filename:str, label:str=None): """Load an image from file. You can optionally set the 'label' keyword.""" self.image = cv2.imread(filename) if label: self.label = label return self def convert_color(self, color:bool): return cv2.cvtColor(self.image, cv2.COLOR_GRAY2BGR if color else cv2.COLOR_BGR2GRAY) def __repr__(self): if self._init_kwargs: kwargstr = ", " + ", ".join([f"{k}={repr(self._init_kwargs[k])}" for k in self._init_kwargs]) else: kwargstr = '' return f"" def copy(self): return np.copy(self.image) def snip(self, rect): assert all((len(rect)==2, len(rect[0])==2, len(rect[1])==2)) #((x,y),(w,h)) return self.image[rect[0][1]:rect[0][1]+rect[1][1], rect[0][0]:rect[0][0]+rect[1][0] ] def mask(self, rect, mask_color=None, nonmask_color=None): assert all((len(rect)==2, len(rect[0])==2, len(rect[1])==2)) #((x,y),(w,h)) if mask_color is None: mask_color = (0, 0, 0) if self.is_color else 0 if nonmask_color is None: nonmask_color = (255, 255, 255) if self.is_color else 255 mask = np.full(self.image.shape, nonmask_color, dtype=np.uint8) cv2.rectangle(mask, *rect, color=mask_color, thickness=cv2.FILLED) return cv2.bitwise_and(self.image, mask) def sift_clusters(self, cluster_radius) -> pointcluster.PointCluster: sift = cv2.SIFT_create() keypoints, descriptions = sift.detectAndCompute(self.image, None) return pointcluster.cluster_set([k.pt for k in keypoints], cluster_radius) @staticmethod def blob_params(*, minThreshold = 10, maxThreshold = 200, minArea = None, maxArea = None, minCircularity = None, maxCircularity = None, minConvexity = None, maxConvexity = None, minInertiaRatio = None, maxInertiaRatio = None): p = cv2.SimpleBlobDetector_Params() p.minThreshold = minThreshold p.maxThreshold = maxThreshold if minArea or maxArea: p.filterByArea = True if minArea: p.minArea = minArea if maxArea: p.maxArea = maxArea if minConvexity or maxConvexity: p.filterByConvexity = True if minConvexity: p.minConvexity = minConvexity if maxConvexity: p.maxConvexity = maxConvexity if minInertiaRatio or maxInertiaRatio: p.filterByInertia = True if minInertiaRatio: p.minInertiaRatio = minInertiaRatio if maxInertiaRatio: p.maxInertiaRatio = maxInertiaRatio if minCircularity or maxCircularity: p.filterByCircularity = True if minCircularity: p.minCircularity = minCircularity if maxCircularity: p.maxCircularity = maxCircularity return p def blob_detect(self, size:int, params=None, invert:bool=False, label:str=None) -> typing.List[Rect]: if params is None: params = CVImage.blob_params() detector = cv2.SimpleBlobDetector_create(params) keypoints = detector.detect(cv2.bitwise_not(self.image) if invert else self.image) rects = [] s = size / 2.0 for kp in keypoints: rects.append(Rect(x=kp.pt[0] - s, y = kp.pt[1] - s, w = size, h = size, label = label or "blob")) return rects def template_detect(self, template:CVImage, threshold:int, dupe_spacing:int) -> typing.List[Rect]: if template.is_color: h, w, _ = template.image.shape else: h, w = template.image.shape if template.is_color != self.is_color: template = CVImage(template.label, template.convert_color(not template.is_color)) res = cv2.matchTemplate(self.image, template.image, cv2.TM_CCOEFF_NORMED) loc = np.where(res >= threshold) rects = [] for pt in zip(*loc[::-1]): if len(rects) > 0: if squared_distance(rects[-1][0], pt) < dupe_spacing: continue rects.append(Rect(x=pt[0], y=pt[1], w=w, h=h, label=template.label)) return rects def show(self, delay=0): cv2.imshow(self.label, self.image) cv2.waitKey(delay) def draw_rect(self, rect:Rect, color=None, text_color=None, text:bool=True, thickness=1): if color is None: color = (255, 255, 255) if self.is_color else 255 cv2.rectangle(self.image, rect.point, rect.point2, color, thickness) if text: self.draw_text(rect.label, rect.point, text_color if text_color else color) def draw_poly(self, points:typing.List[typing.Tuple], closed=True, color=None): if color is None: color = (255, 255, 255) if self.is_color else 255 cv2.polylines(self.image, np.int32([points]), closed, color) def draw_circle(self, center, radius, color=None, thickness = 1): if color is None: color = (255, 255, 255) if self.is_color else 255 cv2.circle(self.image, np.int32(center), np.int32(radius), color, thickness) def draw_text(self, text, point, color): cv2.putText(self.image, text, np.int32(point), cv2.FONT_HERSHEY_PLAIN, 1.0, color) class ImagePipeline: def __init__(self): pass # running this module executes tests if __name__ == '__main__': # initializer for CVImage can load from file img = CVImage("test frame", filename="/home/john/Desktop/Screenshot at 2021-12-19 20-55-22.png") #img.show() # initializer for CVImage can accept a numpy array img_no_title = CVImage("test frame", img.snip( ((0,24),(800,600)) )) #img_no_title.show() #standard rectangle format used throughout the class, avoiding ugly splat operator lives_rect = ((10,10), (190, 65)) lives = CVImage("lives", img_no_title.snip(lives_rect)) lives.show()