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Timestamp Detector

Timestamp extraction module using OCR.

This module provides functionality to extract timestamps from images and videos using optical character recognition (OCR). It includes the TimestampExtractor class which can extract timestamps from: - Static images - Specific frames in video files - The first readable frame in a video file

TimestampExtractor 

TimestampExtractor(
    zone: ndarray = None, allowlist="0123456789-:/"
)

A class for extracting timestamps from images and videos using OCR.

Attributes:

Name Type Description
zone (ndarray, optional)

The coordinates of the timestamp area in the image.
reader Reader

The EasyOCR reader instance for text recognition.
allowlist str

Characters to allow in the OCR process.

Methods:

Name Description
extract_timestamp

Extract timestamp from an image using OCR.
extract_timestamp_video

Extract timestamp from a specific frame in a video file.
extract_timestamp_video_auto

Extract timestamp from the first readable frame in a video file.

Initialize the TimestampExtractor.

Args: zone (np.ndarray): The coordinates of the timestamp area in the image. allowlist (str): Characters to allow in the OCR process.

Source code in src/dnt/detect/timestamp.py 
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def __init__(self, zone: np.ndarray = None, allowlist="0123456789-:/"):
    """Initialize the TimestampExtractor.

    Args:
        zone (np.ndarray): The coordinates of the timestamp area in the image.
        allowlist (str): Characters to allow in the OCR process.

    """
    self.zone = zone
    self.reader = easyocr.Reader(["en"])
    self.allowlist = allowlist

extract_timestamp 

extract_timestamp(
    img: ndarray, gray: bool = False
) -> datetime

Extract timestamp from the image using OCR.

Args: img (np.ndarray): The input image from which to extract the timestamp. gray (bool): Whether to convert the image to grayscale before OCR. returns: datetime: The extracted timestamp.

Source code in src/dnt/detect/timestamp.py 
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def extract_timestamp(
    self,
    img: np.ndarray,
    gray: bool = False,
) -> datetime:
    """Extract timestamp from the image using OCR.

    Args:
        img (np.ndarray): The input image from which to extract the timestamp.
        gray (bool): Whether to convert the image to grayscale before OCR.
    returns:
        datetime: The extracted timestamp.

    """
    # Ensure the zone is a numpy array
    if self.zone is None:
        crop_img = img
    else:
        x1, y1, x2, y2 = self.zone[0][0], self.zone[0][1], self.zone[2][0], self.zone[2][1]
        crop_img = img[y1:y2, x1:x2]

    crop_img = cv2.cvtColor(crop_img, cv2.COLOR_BGR2GRAY) if gray else crop_img

    result = self.reader.readtext(crop_img, detail=0, allowlist="0123456789-:/")
    dt = dateparser.parse(" ".join(result))
    return dt

extract_timestamp_video 

extract_timestamp_video(
    video_path: str, frame: int = 0, gray: bool = False
) -> datetime

Extract timestamp from a video file using OCR.

Args: video_path (str): The path to the video file. frame (int): The frame index to extract the timestamp from. gray (bool): Whether to convert the image to grayscale before OCR. returns: datetime: The extracted timestamp.

Source code in src/dnt/detect/timestamp.py 
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def extract_timestamp_video(
    self,
    video_path: str,
    frame: int = 0,
    gray: bool = False,
) -> datetime:
    """Extract timestamp from a video file using OCR.

    Args:
        video_path (str): The path to the video file.
        frame (int): The frame index to extract the timestamp from.
        gray (bool): Whether to convert the image to grayscale before OCR.
    returns:
        datetime: The extracted timestamp.

    """
    cap = cv2.VideoCapture(video_path)
    cap.set(cv2.CAP_PROP_POS_FRAMES, frame)
    ret, img = cap.read()
    cap.release()

    if not ret:
        raise ValueError("Could not read video file")

    return self.extract_timestamp(img, gray=gray)

extract_timestamp_video_auto 

extract_timestamp_video_auto(
    video_path: str, gray: bool = False
) -> tuple

Extract the initial timestamp from the first readable frame in a video file using OCR.

Args: video_path (str): The path to the video file. gray (bool): Whether to convert the image to grayscale before OCR. returns: dt, frame: The extracted timestamp and the frame index.

Source code in src/dnt/detect/timestamp.py 
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def extract_timestamp_video_auto(
    self,
    video_path: str,
    gray: bool = False,
) -> tuple:
    """Extract the initial timestamp from the first readable frame in a video file using OCR.

    Args:
        video_path (str): The path to the video file.
        gray (bool): Whether to convert the image to grayscale before OCR.
    returns:
        dt, frame: The extracted timestamp and the frame index.

    """
    cap = cv2.VideoCapture(video_path)
    cap.set(cv2.CAP_PROP_POS_FRAMES, 0)
    tot = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))

    for frame in range(0, tot - 1):
        ret, img = cap.read()
        if not ret:
            break
        dt = self.extract_timestamp(img, gray=gray)
        if dt:
            cap.release()
            return dt, frame

    cap.release()
    return None, None