Spaces:
Sleeping
Sleeping
| import gradio as gr | |
| import onnxruntime as ort | |
| import cv2 | |
| import numpy as np | |
| from PIL import Image | |
| import os | |
| import uuid | |
| # 啟動 ONNX 模型 Session | |
| providers = ['CUDAExecutionProvider', 'CPUExecutionProvider'] if ort.get_device() == 'GPU' else ['CPUExecutionProvider'] | |
| session = ort.InferenceSession('AnimeGANv3_Hayao_STYLE_36.onnx', providers=providers) | |
| # 圖片處理 | |
| def process_image(img): | |
| h, w = img.shape[:2] | |
| def to_8s(x): return 256 if x < 256 else x - x % 8 | |
| img = cv2.resize(img, (to_8s(w), to_8s(h))) | |
| img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB).astype(np.float32) / 127.5 - 1.0 | |
| return img | |
| # 圖片轉換 + 下載功能 | |
| def cartoonize_image(input_image): | |
| img = np.array(input_image) | |
| h, w = img.shape[:2] | |
| processed = process_image(img) | |
| processed = np.expand_dims(processed, axis=0) | |
| input_name = session.get_inputs()[0].name | |
| output = session.run(None, {input_name: processed})[0] | |
| result = (np.squeeze(output) + 1.) / 2 * 255 | |
| result = np.clip(result, 0, 255).astype(np.uint8) | |
| result = cv2.resize(result, (w, h)) | |
| result = cv2.cvtColor(result, cv2.COLOR_RGB2BGR) | |
| result_image = Image.fromarray(result) | |
| # 保存下載檔案 | |
| os.makedirs("outputs", exist_ok=True) | |
| filename = f"outputs/{uuid.uuid4().hex}.png" | |
| result_image.save(filename) | |
| return result_image, filename | |
| # Gradio UI | |
| interface = gr.Interface( | |
| fn=cartoonize_image, | |
| inputs=gr.Image(type="pil", label="上傳圖片"), | |
| outputs=[ | |
| gr.Image(type="pil", label="宮崎駿風格轉換結果"), | |
| gr.File(label="⬇️ 下載圖片") | |
| ], | |
| title="🎨 AnimeGANv3 - 宮崎駿風格轉換器", | |
| description="上傳圖片，將自動轉換為宮崎駿動畫風格！", | |
| allow_flagging="never" | |
| ) | |
| interface.launch() | |