Spaces:
Running
Running
| import base64 | |
| import json | |
| import sys | |
| import time | |
| from datetime import datetime | |
| from io import BytesIO | |
| import cv2 | |
| import requests | |
| import base64 | |
| def post_diffusion_transformer(diffusion_transformer_path, url='http://127.0.0.1:7860'): | |
| datas = json.dumps({ | |
| "diffusion_transformer_path": diffusion_transformer_path | |
| }) | |
| r = requests.post(f'{url}/cogvideox_fun/update_diffusion_transformer', data=datas, timeout=1500) | |
| data = r.content.decode('utf-8') | |
| return data | |
| def post_update_edition(edition, url='http://0.0.0.0:7860'): | |
| datas = json.dumps({ | |
| "edition": edition | |
| }) | |
| r = requests.post(f'{url}/cogvideox_fun/update_edition', data=datas, timeout=1500) | |
| data = r.content.decode('utf-8') | |
| return data | |
| def post_infer(generation_method, length_slider, url='http://127.0.0.1:7860'): | |
| datas = json.dumps({ | |
| "base_model_path": "none", | |
| "motion_module_path": "none", | |
| "lora_model_path": "none", | |
| "lora_alpha_slider": 0.55, | |
| "prompt_textbox": "A young woman with beautiful and clear eyes and blonde hair standing and white dress in a forest wearing a crown. She seems to be lost in thought, and the camera focuses on her face. The video is of high quality, and the view is very clear. High quality, masterpiece, best quality, highres, ultra-detailed, fantastic.", | |
| "negative_prompt_textbox": "The video is not of a high quality, it has a low resolution. Watermark present in each frame. The background is solid. Strange body and strange trajectory. Distortion. ", | |
| "sampler_dropdown": "Euler", | |
| "sample_step_slider": 50, | |
| "width_slider": 672, | |
| "height_slider": 384, | |
| "generation_method": "Video Generation", | |
| "length_slider": length_slider, | |
| "cfg_scale_slider": 6, | |
| "seed_textbox": 43, | |
| }) | |
| r = requests.post(f'{url}/cogvideox_fun/infer_forward', data=datas, timeout=1500) | |
| data = r.content.decode('utf-8') | |
| return data | |
| if __name__ == '__main__': | |
| # initiate time | |
| now_date = datetime.now() | |
| time_start = time.time() | |
| # -------------------------- # | |
| # Step 1: update edition | |
| # -------------------------- # | |
| diffusion_transformer_path = "models/Diffusion_Transformer/CogVideoX-Fun-2b-InP" | |
| outputs = post_diffusion_transformer(diffusion_transformer_path) | |
| print('Output update edition: ', outputs) | |
| # -------------------------- # | |
| # Step 2: infer | |
| # -------------------------- # | |
| # "Video Generation" and "Image Generation" | |
| generation_method = "Video Generation" | |
| length_slider = 49 | |
| outputs = post_infer(generation_method, length_slider) | |
| # Get decoded data | |
| outputs = json.loads(outputs) | |
| base64_encoding = outputs["base64_encoding"] | |
| decoded_data = base64.b64decode(base64_encoding) | |
| is_image = True if generation_method == "Image Generation" else False | |
| if is_image or length_slider == 1: | |
| file_path = "1.png" | |
| else: | |
| file_path = "1.mp4" | |
| with open(file_path, "wb") as file: | |
| file.write(decoded_data) | |
| # End of record time | |
| # The calculated time difference is the execution time of the program, expressed in seconds / s | |
| time_end = time.time() | |
| time_sum = (time_end - time_start) % 60 | |
| print('# --------------------------------------------------------- #') | |
| print(f'# Total expenditure: {time_sum}s') | |
| print('# --------------------------------------------------------- #') |