| 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() |
|
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