| from PIL import Image, ImageDraw, ImageFont |
| import numpy as np |
| import torch |
| from inference import load_model, preprocess_image, predict |
|
|
| original_img = Image.open("DUTS-TR-Image/ILSVRC2012_test_00000645.jpg").convert("RGB") |
|
|
| background_with_text = original_img.copy() |
| draw = ImageDraw.Draw(background_with_text) |
| font_size = 50 |
| font = ImageFont.truetype("/usr/share/fonts/truetype/freefont/FreeSansBold.ttf", font_size) |
| text = "Hello, world!" |
| text_position = (50, 50) |
| text_color = (255, 255, 255) |
| draw.text(text_position, text, fill=text_color, font=font) |
|
|
| device = torch.device("cuda" if torch.cuda.is_available() else "cpu") |
| weights_path = "unet_model.pth" |
| model = load_model(weights_path, device) |
| image_tensor = preprocess_image("DUTS-TR-Image/ILSVRC2012_test_00000645.jpg") |
| mask = predict(model, image_tensor, device) |
|
|
| print(mask.shape) |
|
|
| mask = mask.squeeze(0) |
| mask_binary = (mask > 0.5).astype(np.uint8) * 255 |
| mask_img = Image.fromarray(mask_binary, mode="L") |
| mask_img = mask_img.resize(original_img.size, resample=Image.NEAREST) |
|
|
| original_rgba = original_img.convert("RGBA") |
|
|
| r, g, b, _ = original_rgba.split() |
| subject_img = Image.merge("RGBA", (r, g, b, mask_img)) |
|
|
| background_with_text.paste(subject_img, (0, 0), subject_img) |
| background_with_text.save("final_output.png") |
