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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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