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| import onnxruntime | |
| print(onnxruntime.get_device()) | |
| import os | |
| import gradio as gr | |
| os.system("pip install gdown") | |
| os.system("gdown https://drive.google.com/uc?id=1riNxV1BWMAXfmWZ3LrQbEkvzV8f7lOCp") | |
| opts = onnxruntime.SessionOptions() | |
| opts.intra_op_num_threads = 16 | |
| onnx_session = onnxruntime.InferenceSession("/home/user/app/face_paint_512_v2_0.onnx",sess_options=opts) | |
| input_name = onnx_session.get_inputs()[0].name | |
| output_name = onnx_session.get_outputs()[0].name | |
| side_length = 512 | |
| import cv2 as cv | |
| import numpy as np | |
| from PIL import Image | |
| def inference(img): | |
| image = np.array(img) | |
| image = image[:, :, ::-1].copy() | |
| image = cv.resize(image, dsize=(side_length, side_length)) | |
| x = cv.cvtColor(image, cv.COLOR_BGR2RGB) | |
| x = np.array(x, dtype=np.float32) | |
| x = x.transpose(2, 0, 1) | |
| x = x * 2 - 1 | |
| x = x.reshape(-1, 3, side_length, side_length) | |
| onnx_result = onnx_session.run([output_name], {input_name: x}) | |
| onnx_result = np.array(onnx_result).squeeze() | |
| onnx_result = (onnx_result * 0.5 + 0.5).clip(0, 1) | |
| onnx_result = onnx_result * 255 | |
| onnx_result = onnx_result.transpose(1, 2, 0).astype('uint8') | |
| onnx_result = cv.cvtColor(onnx_result, cv.COLOR_RGB2BGR) | |
| img = cv.cvtColor(onnx_result, cv.COLOR_BGR2RGB) | |
| im_pil = Image.fromarray(img) | |
| return im_pil | |
| title = "Animeganv2" | |
| description = "Gradio demo for AnimeGanv2 Face Portrait v2. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below." | |
| article = "<p style='text-align: center'><a href='https://github.com/bryandlee/animegan2-pytorch' target='_blank'>Github Repo Pytorch</a> | <a href='https://github.com/Kazuhito00/AnimeGANv2-ONNX-Sample' target='_blank'>Github Repo ONNX</a></p><p style='text-align: center'>samples from repo: <img src='https://user-images.githubusercontent.com/26464535/129888683-98bb6283-7bb8-4d1a-a04a-e795f5858dcf.gif' alt='animation'/> <img src='https://user-images.githubusercontent.com/26464535/137619176-59620b59-4e20-4d98-9559-a424f86b7f24.jpg' alt='animation'/></p>" | |
| gr.Interface(inference, gr.inputs.Image(type="pil", source="webcam"), gr.outputs.Image(type="pil"),title=title,description=description,article=article,enable_queue=True,live=True).launch() |