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()