camera_config.py

import time
import cv2
import os
from datetime import datetime
from vehicle_calculations import *
from parameters_config import *

import os
from datetime import datetime


def create_unique_filename(folder_path, model_tag, extension=".mp4"):
    os.makedirs(folder_path, exist_ok=True)

    timestamp = datetime.now().strftime("%Y-%m-%d_%H-%M-%S")

    filename = f"{timestamp}_{model_tag}{extension}"
    full_path = os.path.join(folder_path, filename)

    return full_path


def draw_boxes(results, frame_resized, prev_positions, time_elapsed):
    for result in results:
        boxes = result.boxes
        for i in range(len(boxes)):
            box = boxes.xyxy[i].numpy().astype(int)
            confidence = float(boxes.conf[i].numpy())
            class_id = int(boxes.cls[i].numpy())
            label = model.names[class_id]

            if label in TARGETS:
                x1, y1, x2, y2 = box
                center = ((x1 + x2) // 2, (y1 + y2) // 2)
                track_id = (label, i)
                  

                if label != "person":
                    trackMPH(prev_positions, track_id, center, time_elapsed, frame_resized, x1, y1)
                

                # Draw box and label
                color = (0, 0, 255)
                cv2.rectangle(frame_resized, (x1, y1), (x2, y2), color, 2)
                cv2.putText(frame_resized, f"{label} {confidence:.2f}", (x1, y1 - 10),
                            cv2.FONT_HERSHEY_SIMPLEX, 0.5, color, 2)



def runWebCam(prev_positions, prev_frame_time, VIDEO_PATH, video, show_window):

    if video:
      video = model(VIDEO_PATH)
      window_title = "Fake Webcam"
    else:
      video = 0 #For webcam
      window_title = "YOLO Webcam"

      cap = cv2.VideoCapture(video)
      if not cap.isOpened():
        raise Exception("Error: Could not open video stream or file.")
    show_window = True

    video_fps = cap.get(cv2.CAP_PROP_FPS)
    fourcc = cv2.VideoWriter_fourcc(*"mp4v")
    
    
    output_path = create_unique_filename(folder_path="output_video", model_tag = os.path.splitext(os.path.basename(model_path))[0])
    print("Video will be saved to:", output_path)

    out = cv2.VideoWriter(output_path, fourcc, video_fps, (WIDTH, HEIGHT))
    
    if not out.isOpened():
        raise Exception(f"Failed to open video writer with path: {output_path}")



    try:
        while True:
            ret, frame = cap.read()
            if not ret:
                print("End of video or failed to read frame.")
                break  


            # Capture time at start of frame
            new_frame_time = time.time()
            time_elapsed = new_frame_time - prev_frame_time
            fps = 1 / time_elapsed if time_elapsed > 0 else 1

            # Resize and preprocess
            frame_resized = cv2.resize(frame, (WIDTH, HEIGHT))
            frame_rgb = cv2.cvtColor(frame_resized, cv2.COLOR_BGR2RGB)

            # Inference
            results = model(frame_rgb)

            # Draw boxes and calculate speed
            draw_boxes(results, frame_resized, prev_positions, time_elapsed)

            # Display FPS
            cv2.putText(frame_resized, f"FPS: {fps:.2f}", (10, 30),
                        cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)



            out.write(frame_resized)



            if show_window:
                # Show result
                cv2.imshow(window_title, frame_resized)

                # Break condition
                if cv2.waitKey(1) & 0xFF == ord('q'):
                    break

            # Update time after drawing
            prev_frame_time = new_frame_time


    finally:
        cap.release()
        out.release()
        if show_window:
            cv2.destroyAllWindows()