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import cv2 |
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import numpy as np |
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import gradio as gr |
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def create_mask(frame): |
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"""Frame'de kırmızı renk maskesi oluşturur.""" |
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hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV) |
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mask1 = cv2.inRange(hsv, (0, 120, 70), (10, 255, 255)) |
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mask2 = cv2.inRange(hsv, (170, 120, 70), (180, 255, 255)) |
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mask = mask1 | mask2 |
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return mask |
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def apply_morphology(mask, kernel_size=15): |
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"""Maskeye morfolojik işlemler uygular.""" |
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kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (kernel_size, kernel_size)) |
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morph = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, kernel) |
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return morph |
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def find_largest_component(morph): |
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"""En büyük bağlı bileşenin merkezini bulur.""" |
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num_labels, labels, stats, centroids = cv2.connectedComponentsWithStats(morph, connectivity=8) |
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if num_labels > 1: |
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largest_label = 1 + np.argmax(stats[1:, cv2.CC_STAT_AREA]) |
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cX = int(centroids[largest_label][0]) |
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cY = int(centroids[largest_label][1]) |
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return cX, cY |
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else: |
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return None |
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def draw_trajectory(frame, trajectory): |
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"""Topun izlediği yolu çizer.""" |
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if len(trajectory) > 1: |
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pts = np.array(trajectory, np.int32) |
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pts = pts.reshape((-1, 1, 2)) |
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cv2.polylines(frame, [pts], False, (0, 255, 0), 2) |
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def analyze_trajectory(trajectory, std_threshold=10): |
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"""Trajektori analizini yapar.""" |
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if len(trajectory) < 2: |
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return "Yolu belirlemek için yeterli veri yok." |
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else: |
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x_coords = np.array(trajectory)[:, 0] |
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std_x = np.std(x_coords) |
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return "ok" if std_x < std_threshold else "not ok" |
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def process_video(video, kernel_size=15, std_threshold=10): |
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"""Videoyu işler ve topun yörüngesini analiz eder.""" |
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try: |
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cap = cv2.VideoCapture(video) |
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fps = cap.get(cv2.CAP_PROP_FPS) |
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_, frame = cap.read() |
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if frame is None: |
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return "Videodan çerçeve okunamadı!", None, None |
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fourcc = cv2.VideoWriter_fourcc(*'XVID') |
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height, width = frame.shape[:2] |
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try: |
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out_mask = cv2.VideoWriter('mask_output.avi', fourcc, fps, (width, height), False) |
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out_final = cv2.VideoWriter('output.avi', fourcc, fps, (width, height)) |
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except: |
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return "Video dosyaları oluşturulamadı!", None, None |
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trajectory = [] |
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while cap.isOpened(): |
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ret, frame = cap.read() |
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if not ret: |
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break |
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mask = create_mask(frame) |
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out_mask.write(mask) |
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morph = apply_morphology(mask, kernel_size) |
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center = find_largest_component(morph) |
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if center: |
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cX, cY = center |
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trajectory.append((cX, cY)) |
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cv2.circle(frame, (cX, cY), 5, (0, 255, 0), -1) |
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draw_trajectory(frame, trajectory) |
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out_final.write(frame) |
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cap.release() |
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out_mask.release() |
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out_final.release() |
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result_text = analyze_trajectory(trajectory, std_threshold) |
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return result_text, 'mask_output.avi', 'output.avi' |
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except: |
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return "Video işlenirken bir hata oluştu!", None, None |
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demo = gr.Interface( |
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fn=process_video, |
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inputs=[ |
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gr.Video(label="Girdi Video"), |
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gr.Slider(1, 50, value=15, step=1, label="Kernel Boyutu"), |
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gr.Slider(1, 100, value=10, step=1, label="Standart Sapma Eşiği") |
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], |
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outputs=[ |
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gr.Textbox(label="Yol Analiz Sonucu"), |
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gr.Video(label="Maske Video"), |
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gr.Video(label="Çıktı Video") |
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], |
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examples=[ |
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["ok.mp4", 15, 10], |
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["not_ok1.mp4", 15, 10], |
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["not_ok2.mp4", 15, 10] |
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] |
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) |
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if __name__ == "__main__": |
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demo.launch(show_error=True) |
