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import cv2
import av
import numpy as np
def resize_aspect_fit(image, dim=(640, 480)):
h, w = image.shape[:2]
aspect_ratio = w / h
target_width, target_height = dim
target_aspect = target_width / target_height
if aspect_ratio > target_aspect:
# Original aspect is wider than target
new_width = target_width
new_height = int(target_width / aspect_ratio)
else:
# Original aspect is taller than target
new_height = target_height
new_width = int(target_height * aspect_ratio)
resized_image = cv2.resize(image, (new_width, new_height), interpolation=cv2.INTER_AREA)
return resized_image
def resize_and_crop(image, dim=(640, 480)):
h, w = image.shape[:2]
aspect_ratio = w / h
target_width, target_height = dim
target_aspect = target_width / target_height
if aspect_ratio > target_aspect:
# Original aspect is wider than target, fit by height
new_height = target_height
new_width = int(target_height * aspect_ratio)
else:
# Original aspect is taller than target, fit by width
new_width = target_width
new_height = int(target_width / aspect_ratio)
# Resize the image with new dimensions
resized_image = cv2.resize(image, (new_width, new_height), interpolation=cv2.INTER_AREA)
# Crop to target dimensions
x_offset = (new_width - target_width) // 2
y_offset = (new_height - target_height) // 2
cropped_image = resized_image[y_offset:y_offset + target_height, x_offset:x_offset + target_width]
return cropped_image
def overlay_images(background, overlay, x, y):
"""
Overlay an image with transparency over another image.
"""
# Check if overlay dimensions fit within the background at the given (x, y) position
if y + overlay.shape[0] > background.shape[0] or x + overlay.shape[1] > background.shape[1]:
raise ValueError("Overlay dimensions exceed background dimensions at the specified position.")
# Extract the alpha channel from the overlay and create an inverse alpha channel
alpha = overlay[:, :, 3] / 255.0
inverse_alpha = 1.0 - alpha
# Convert overlay to BGR if it's in RGB
if overlay.shape[2] == 4: # If it has an alpha channel
overlay = cv2.cvtColor(overlay[:, :, :3], cv2.COLOR_RGB2BGR)
overlay = np.concatenate([overlay, overlay[:, :, 3:]], axis=2) # Add alpha channel back
else:
overlay = cv2.cvtColor(overlay, cv2.COLOR_RGB2BGR)
# Overlay the images
for c in range(0, 3):
background[y:overlay.shape[0]+y, x:overlay.shape[1]+x, c] = (
alpha * overlay[:, :, c] + inverse_alpha * background[y:overlay.shape[0]+y, x:overlay.shape[1]+x, c]
)
return background
def transform_frame(user_frame: av.VideoFrame) -> av.VideoFrame:
# Convert av.VideoFrame to numpy array (OpenCV format)
user_frame_np = np.frombuffer(user_frame.planes[0], np.uint8).reshape(user_frame.height, user_frame.width, -1)
# Load background image
background = cv2.imread("zoom-background.png")
# Load bot image (assuming it has an alpha channel for transparency)
bot_image = cv2.imread("bot-image.png", cv2.IMREAD_UNCHANGED)
# Resize background to match the user frame dimensions
aspect_ratio = background.shape[1] / background.shape[0]
new_h = user_frame.height
new_w = int(new_h * aspect_ratio)
background_resized = cv2.resize(background, (new_w, new_h))
# Crop the background if it exceeds the user frame width
if new_w > user_frame.width:
crop_x1 = (new_w - user_frame.width) // 2
crop_x2 = crop_x1 + user_frame.width
background_resized = background_resized[:, crop_x1:crop_x2, :3]
# Overlay bot image on the right-hand side
x_bot = background_resized.shape[1] - bot_image.shape[1]
y_bot = 0
background_resized = overlay_images(background_resized, bot_image, x_bot, y_bot)
# Overlay user's video frame in the bottom-left corner
x_user = 0
y_user = background_resized.shape[0] - user_frame.height
background_resized[y_user:user_frame.height+y_user, x_user:user_frame.width+x_user, :3] = user_frame_np
# Convert the final frame back to av.VideoFrame
output_frame = av.VideoFrame.from_ndarray(background_resized, format="bgr24")
return output_frame
def create_charles_frames(background, charles_frames):
output_frames = []
# Load background image
background = cv2.imread(background, cv2.COLOR_BGR2RGB)
background = cv2.cvtColor(background, cv2.COLOR_BGR2RGB)
# resize background to match user image
background = resize_and_crop(background, (640, 480))
for bot_image_path in charles_frames:
bot_image = cv2.imread(bot_image_path, cv2.IMREAD_UNCHANGED)
# assert bot image is square
assert bot_image.shape[0] == bot_image.shape[1]
# resize bot image if it is larger than backgroun impage in any direction
if bot_image.shape[0] > background.shape[0]:
bot_image = cv2.resize(bot_image, (background.shape[0], background.shape[0]), interpolation=cv2.INTER_AREA)
# Overlay bot image on the right-hand side
x_bot = background.shape[1] - bot_image.shape[1]
y_bot = background.shape[0] - bot_image.shape[0]
background_with_bot = overlay_images(background.copy(), bot_image, x_bot, y_bot)
output_frames.append(background_with_bot)
return output_frames
def test_create_bot_frames():
frames = create_charles_frames("./images/zoom-background.png", ["./images/charles.png", "./images/charles-open.png"])
index = 0
for frame in frames:
final_frame_bgr = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)
cv2.imwrite(f"./images/charles_frame_{index}.jpg", final_frame_bgr)
index += 1
def test_overlay():
# Load mock user image
user_image = cv2.imread("./prototypes/person-016.jpg", cv2.COLOR_BGR2RGB)
user_image = cv2.cvtColor(user_image, cv2.COLOR_BGR2RGB)
# resize to 640x480, handle that this is smaller and can be cropped
user_image = resize_and_crop(user_image, (640, 480))
# Load background image
background = cv2.imread("./images/zoom-background.png", cv2.COLOR_BGR2RGB)
background = cv2.cvtColor(background, cv2.COLOR_BGR2RGB)
# resize background to match user image
background = resize_and_crop(background, (user_image.shape[:2][1], user_image.shape[:2][0]))
# Load bot image (assuming it has an alpha channel for transparency)
bot_image = cv2.imread("./images/charles-open.png", cv2.IMREAD_UNCHANGED)
# resize bot image if it is larger than backgroun impage in any direction
if bot_image.shape[0] > background.shape[0]:
bot_image = cv2.resize(bot_image, (background.shape[0], background.shape[0]), interpolation=cv2.INTER_AREA)
# Overlay bot image on the right-hand side
x_bot = background.shape[1] - bot_image.shape[1]
y_bot = background.shape[0] - bot_image.shape[0]
background_with_bot = overlay_images(background.copy(), bot_image, x_bot, y_bot)
# Overlay user's frame in the bottom-left corner (1/3 size)
# resize user image to 1/4 size
user_frame = cv2.resize(user_image, (user_image.shape[1]//4, user_image.shape[0]//4), interpolation=cv2.INTER_AREA)
x_user = 0
y_user = background.shape[0] - user_frame.shape[0]
final_frame = background_with_bot.copy()
# final_frame[y_user:user_frame.shape[0]+y_user, x_user:user_frame.shape[1]+x_user, :3] = user_frame
final_frame[y_user:y_user+user_frame.shape[0], x_user:x_user+user_frame.shape[1]] = user_frame
# Save the final frame as JPEG
final_frame_bgr = cv2.cvtColor(final_frame, cv2.COLOR_RGB2BGR)
cv2.imwrite("./images/final_frame.jpg", final_frame_bgr)
test_overlay()
test_create_bot_frames() |