TIF_E41200329/Python/mycobacterium.py

54 lines
1.5 KiB
Python

import cv2
import os
import numpy as np
# Path folder gambar
image_folder = 'D:/Skripsi/ekstraksi fitur/Mycobacterium Tuberculosis'
# Cek apakah folder gambar ada
if not os.path.isdir(image_folder):
print(f"Folder {image_folder} tidak ditemukan.")
exit()
# Jumlah gambar dalam folder
image_files = [f for f in os.listdir(image_folder) if f.endswith('.jpg')]
num_images = len(image_files)
# Baris citra
row = 1
for i in range(num_images):
file_name = f'{image_folder}/{image_files[i]}'
# Preprocessing
img = cv2.imread(file_name, 1)
if img is None:
print(f"Gagal membaca file: {file_name}")
continue
blue, green, red = cv2.split(img)
# Thresholding
ret, img_bin = cv2.threshold(green, 135, 255, cv2.THRESH_BINARY_INV)
img_bin = cv2.dilate(img_bin, None, iterations=1)
# Labeling objek
num_labels, labels, stats, centroids = cv2.connectedComponentsWithStats(img_bin, connectivity=8)
# Inisialisasi mask kosong
mask = np.zeros_like(img_bin)
# Ukuran minimum dan maksimum objek yang ingin dipertahankan
min_size = 50
max_size = 400
# Iterasi melalui semua objek dan hanya pertahankan yang ukurannya di antara min_size dan max_size
for j in range(1, num_labels): # Mulai dari 1 untuk melewatkan background
if min_size <= stats[j, cv2.CC_STAT_AREA] <= max_size:
mask[labels == j] = 255
# Display hasilnya
cv2.imshow("Original", img_bin)
cv2.waitKey(800)
cv2.imshow("Filtered", mask)
cv2.waitKey(800)
cv2.destroyAllWindows()