【AI-Shorts-Creator】Youtubeの切り抜きをAIで自動化してショートを量産する方法

■Pythonのバージョン
Python 3.x

■必要なパッケージ
pytube
opencv-python 
openai==0.28 
youtube-transcript-api
FFmpeg 

git clone https://github.com/NisaarAgharia/AI-Shorts-Creator.git

pip install -r requirements.txt

pip install openai==0.28

python auto_cropper.py

python auto_cropper.py

import cv2

def crop_video(faces, input_file, output_file):
    try:
        if len(faces) > 0:
            # Constants for cropping
            CROP_RATIO = 0.9  # Adjust the ratio to control how much of the face is visible in the cropped video
            VERTICAL_RATIO = 9 / 16  # Aspect ratio for the vertical video

            # Read the input video
            cap = cv2.VideoCapture(input_file)

            # Get the frame dimensions
            frame_width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
            frame_height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))

            # Calculate the target width and height for cropping (vertical format)
            target_height = int(frame_height * CROP_RATIO)
            target_width = int(target_height * VERTICAL_RATIO)

            # Create a VideoWriter object to save the output video
            fourcc = cv2.VideoWriter_fourcc(*"mp4v")
            output_video = cv2.VideoWriter(output_file, fourcc, 60.0, (target_width, target_height))

            # Loop through each frame of the input video
            while True:
                ret, frame = cap.read()

                # If no more frames, break out of the loop
                if not ret:
                    break

                # Iterate through each detected face
                for face in faces:
                    # Unpack the face coordinates
                    x, y, w, h = face

                    # Calculate the crop coordinates
                    crop_x = max(0, x + (w - target_width) // 2)  # Adjust the crop region to center the face
                    crop_y = max(0, y + (h - target_height) // 2)
                    crop_x2 = min(crop_x + target_width, frame_width)
                    crop_y2 = min(crop_y + target_height, frame_height)

                    # Crop the frame based on the calculated crop coordinates
                    cropped_frame = frame[crop_y:crop_y2, crop_x:crop_x2]

                    # Resize the cropped frame to the target dimensions
                    resized_frame = cv2.resize(cropped_frame, (target_width, target_height))

                    # Write the resized frame to the output video
                    output_video.write(resized_frame)

            # Release the input and output video objects
            cap.release()
            output_video.release()

            print("Video cropped successfully.")
        else:
            print("No faces detected in the video.")
    except Exception as e:
        print(f"Error during video cropping: {str(e)}")

import cv2

def crop_video(faces, input_file, output_file):
    try:
        if len(faces) > 0:
            # Constants for cropping
            CROP_RATIO = 0.9
            VERTICAL_RATIO = 9 / 16

            cap = cv2.VideoCapture(input_file)
            frame_width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
            frame_height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
            frame_rate = cap.get(cv2.CAP_PROP_FPS)  # Get the frame rate of the original video

            target_height = int(frame_height * CROP_RATIO)
            target_width = int(target_height * VERTICAL_RATIO)

            # Create a VideoWriter object
            fourcc = cv2.VideoWriter_fourcc(*"mp4v")
            out = cv2.VideoWriter(output_file, fourcc, frame_rate, (target_width, target_height))

            while True:
                ret, frame = cap.read()
                if not ret:
                    break

                # Use the first detected face for cropping
                x, y, w, h = faces[0]
                x_center = x + w // 2
                y_center = y + h // 2

                # Calculate crop coordinates
                x1 = max(0, x_center - target_width // 2)
                x2 = min(frame_width, x_center + target_width // 2)
                y1 = max(0, y_center - target_height // 2)
                y2 = min(frame_height, y_center + target_height // 2)

                # Crop and resize the frame
                cropped_frame = frame[y1:y2, x1:x2]
                resized_frame = cv2.resize(cropped_frame, (target_width, target_height))

                out.write(resized_frame)

            cap.release()
            out.release()
            print("Cropping and resizing completed successfully.")
        else:
            print("No faces detected.")
    except Exception as e:
        print(f"Error: {e}")