Create README.md

README.md

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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()
+
+
+