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def frame_to_timecode(frame_num, total_frames, duration):
total_seconds = (frame_num / total_frames) * duration
hours = int(total_seconds // 3600)
minutes = int((total_seconds % 3600) // 60)
seconds = int(total_seconds % 60)
milliseconds = int((total_seconds - int(total_seconds)) * 1000)
return f"{hours:02d}:{minutes:02d}:{seconds:02d}.{milliseconds:03d}"
def seconds_to_timecode(seconds):
hours = int(seconds // 3600)
minutes = int((seconds % 3600) // 60)
seconds = int(seconds % 60)
return f"{hours:02d}:{minutes:02d}:{seconds:02d}"
def timecode_to_seconds(timecode):
h, m, s = map(int, timecode.split(':'))
return h * 3600 + m * 60 + s
def add_timecode_to_image(image, timecode):
from PIL import Image, ImageDraw, ImageFont
import numpy as np
img_pil = Image.fromarray(image)
draw = ImageDraw.Draw(img_pil)
font = ImageFont.truetype("arial.ttf", 15)
draw.text((10, 10), timecode, (255, 0, 0), font=font)
return np.array(img_pil)
def add_timecode_to_image_body(image, timecode):
from PIL import Image, ImageDraw, ImageFont
import numpy as np
img_pil = Image.fromarray(image)
draw = ImageDraw.Draw(img_pil)
font = ImageFont.truetype("arial.ttf", 100)
draw.text((10, 10), timecode, (255, 0, 0), font=font)
return np.array(img_pil)
def create_annotated_video(video_path, df, mse_embeddings, largest_cluster, output_path):
video = cv2.VideoCapture(video_path)
fps = video.get(cv2.CAP_PROP_FPS)
width = int(video.get(cv2.CAP_PROP_FRAME_WIDTH))
height = int(video.get(cv2.CAP_PROP_FRAME_HEIGHT))
fourcc = cv2.VideoWriter_fourcc(*'mp4v')
out = cv2.VideoWriter(output_path, fourcc, fps, (width, height))
frame_number = 0
while True:
ret, frame = video.read()
if not ret:
break
# Detect face and draw bounding box
boxes, _ = mtcnn.detect(frame)
if boxes is not None and len(boxes) > 0:
box = boxes[0]
cv2.rectangle(frame, (int(box[0]), int(box[1])), (int(box[2]), int(box[3])), (0, 255, 0), 2)
# Draw facial landmarks
face_mesh_results = face_mesh.process(cv2.cvtColor(frame, cv2.COLOR_BGR2RGB))
if face_mesh_results.multi_face_landmarks:
for face_landmarks in face_mesh_results.multi_face_landmarks:
mp_drawing.draw_landmarks(
image=frame,
landmark_list=face_landmarks,
connections=mp_face_mesh.FACEMESH_TESSELATION,
landmark_drawing_spec=None,
connection_drawing_spec=mp_drawing_styles.get_default_face_mesh_tesselation_style()
)
# Add MSE annotation
if frame_number in df['Frame'].values:
mse = mse_embeddings[df['Frame'] == frame_number].iloc[0]
cv2.putText(frame, f"MSE: {mse:.4f}", (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2)
out.write(frame)
frame_number += 1
video.release()
out.release() |