| import cv2 | |
| import tkinter as tk | |
| from tkinter import filedialog | |
| def save_image(): | |
| filename = filedialog.asksaveasfilename(defaultextension='.jpg') | |
| if filename: | |
| cv2.imwrite(filename, frame) | |
| def update_params(): | |
| detector = cv2.SimpleBlobDetector_create(params) | |
| def update_sliders(): | |
| min_size_slider.set(params.minArea) | |
| max_size_slider.set(params.maxArea) | |
| threshold_slider.set(params.thresholdStep) | |
| def on_value_changed(value): | |
| if value == "min_size": | |
| params.minArea = min_size_slider.get() | |
| elif value == "max_size": | |
| params.maxArea = max_size_slider.get() | |
| elif value == "threshold": | |
| params.thresholdStep = threshold_slider.get() | |
| update_params() | |
| cap = cv2.VideoCapture(0) | |
| cap.set(cv2.CAP_PROP_FRAME_WIDTH, 640) | |
| cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 480) | |
| params = cv2.SimpleBlobDetector_Params() | |
| params.filterByArea = True | |
| params.minArea = 1 | |
| params.maxArea = 5000 | |
| params.thresholdStep = 10 | |
| detector = cv2.SimpleBlobDetector_create(params) | |
| root = tk.Tk() | |
| root.title("Detector de microparticulas") | |
| min_size_label = tk.Label(root, text="Tamaño minimo") | |
| min_size_slider = tk.Scale(root, from_=0, to=1000, length=200, orient=tk.HORIZONTAL, label="Tamaño mínimo", command=lambda value: on_value_changed("min_size")) | |
| max_size_label = tk.Label(root, text="Tamaño maximo") | |
| max_size_slider = tk.Scale(root, from_=0, to=10000, length=200, orient=tk.HORIZONTAL, label="Tamaño máximo", command=lambda value: on_value_changed("max_size")) | |
| threshold_label = tk.Label(root, text="Sensibilidad") | |
| threshold_slider = tk.Scale(root, from_=0, to=255, length=200, orient=tk.HORIZONTAL, label="Sensibilidad", command=lambda value: on_value_changed("threshold")) | |
| min_dist_label = tk.Label(root, text="Distancia minima entre blobs") | |
| min_dist_slider = tk.Scale(root, from_=0, to=100, length=200, orient=tk.HORIZONTAL, label="Distancia minima", command=lambda value: on_value_changed("min_dist")) | |
| circularity_label = tk.Label(root, text="Circulatidad") | |
| circularity_slider = tk.Scale(root, from_=0, to=1, resolution=0.1, length=200, orient=tk.HORIZONTAL, label="Circulatidad", command=lambda value: on_value_changed("circularity")) | |
| convexity_label = tk.Label(root, text="Convexidad") | |
| convexity_slider = tk.Scale(root, from_=0, to=1, resolution=0.1, length=200, orient=tk.HORIZONTAL, label="Convexidad", command=lambda value: on_value_changed("convexity")) | |
| inertia_label = tk.Label(root, text="Inercia") | |
| inertia_slider = tk.Scale(root, from_=0, to=1, resolution=0.1, length=200, orient=tk.HORIZONTAL, label="Inercia", command=lambda value: on_value_changed("inertia")) | |
| save_button = tk.Button(root, text="Guardar imagen", command=save_image) | |
| min_size_label.pack() | |
| min_size_slider.pack() | |
| max_size_label.pack() | |
| max_size_slider.pack() | |
| threshold_label.pack() | |
| threshold_slider.pack() | |
| min_dist_label.pack() | |
| min_dist_slider.pack() | |
| circularity_label.pack() | |
| circularity_slider.pack() | |
| update_params() | |
| update_sliders() | |
| while True: | |
| ret, frame = cap.read() | |
| if not ret: | |
| continue | |
| gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) | |
| keypoints = detector.detect(gray) | |
| if keypoints: | |
| for kp in keypoints: | |
| x, y = kp.pt | |
| size = kp.size | |
| cv2.rectangle(frame, (int(x - size / 2), int(y - size / 2)), (int(x + size / 2), int(y + size / 2)), (0, 255, 0), 2) | |
| count = len(keypoints) | |
| cv2.putText(frame, "Contador: " + str(count), (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2) | |
| cv2.imshow("Detector de micropartículas", frame) | |
| key = cv2.waitKey(1) | |
| if key == ord('q'): | |
| break | |
| elif key == ord('+'): | |
| params.maxArea += 5000 | |
| update_sliders() | |
| elif key == ord('-'): | |
| params.maxArea -= 5000 | |
| update_sliders() | |
| cap.release() | |
| cv2.destroyAllWindows() | |