Rodin.py

import socketio
import requests
import json
import time
import random
import base64
import io
from PIL import Image
from io import BytesIO
from requests_toolbelt.multipart.encoder import MultipartEncoder
from constant import *


def login(email, password):
    payload = {'password': password}
    if email:
        payload['email'] = email
    
    response = requests.post(f"{BASE_URL}/user/login", json=payload)
    try:
        response_data = response.json()
    except json.JSONDecodeError as e:
        log("ERROR", f"Error in login: {response}")
        raise e
    
    if 'error' in response_data and response_data['error']:
        raise Exception(response_data['error'])
    log("INFO", f"Logged successfully")
    user_uuid = response_data['user_uuid']
    token = response_data['token']
    print(user_uuid, token)
    
    return user_uuid, token

def rodin_history(task_uuid, token):
    headers = {
        'Authorization': f'Bearer {token}'
    }
    response = requests.post(f"{BASE_URL}/task/rodin_history", data={"uuid": task_uuid}, headers=headers)
    return response.json()

def rodin_preprocess_image(generate_prompt, image, name, token):
    m = MultipartEncoder(
        fields={
            'generate_prompt': "true" if generate_prompt else "false",
            'images': (name, image, 'image/jpeg')
        }
    )
    headers = {
        'Content-Type': m.content_type,
        'Authorization': f'Bearer {token}'
    }
    response = requests.post(f"{BASE_URL}/task/rodin_mesh_image_process", data=m, headers=headers)
    return response.json()

def crop_image(image, type):
    new_image_width = 360 * (11520 // 720)  # 每隔720像素裁切一次，每次裁切宽度为360
    new_image_height = 360  # 新图片的高度
    new_image = Image.new('RGB', (new_image_width, new_image_height))

    for i in range(11520 // 720):
        left = i * 720 + type[1]
        upper = type[0]
        right = left + 360
        lower = upper + 360
        cropped_image = image.crop((left, upper, right, lower))
        new_image.paste(cropped_image, (i * 360, 0))
    return new_image

# Perform Rodin mesh operation
def rodin_mesh(prompt, group_uuid, settings, images, name, token):
    images = [convert_base64_to_binary(img) for img in images]
    
    m = MultipartEncoder(
        fields={
            'prompt': prompt,
            'group_uuid': group_uuid,
            'settings': json.dumps(settings),  # Convert settings dictionary to JSON string
            **{f'images': (name, image, 'image/jpeg') for i, image in enumerate(images)}
        }
    )

    headers = {
        'Content-Type': m.content_type,
        'Authorization': f'Bearer {token}'
    }
    response = requests.post(f"{BASE_URL}/task/rodin_mesh", data=m, headers=headers)
    return response.json()

# Convert base64 to binary since the result from `rodin_preprocess_image` is encoded with base64
def convert_base64_to_binary(base64_string):
    if ',' in base64_string:
        base64_string = base64_string.split(',')[1]
        
    image_data = base64.b64decode(base64_string)
    image_buffer = io.BytesIO(image_data)
    
    return image_buffer

def rodin_update(prompt, task_uuid, token, settings):
    headers = {
        'Authorization': f'Bearer {token}'
    }
    response = requests.post(f"{BASE_URL}/task/rodin_update", data={"uuid": task_uuid, "prompt": prompt, "settings": settings}, headers=headers)
    return response.json()

def load_image(img_path):
    image = Image.open(img_path)

    # 按比例缩小图像到长度为1024
    width, height = image.size
    if width > height:
        scale = 1024 / width
    else:
        scale = 1024 / height
    new_width = int(width * scale)
    new_height = int(height * scale)
    resized_image = image.resize((new_width, new_height))

    # 将 PIL.Image 对象转换为字节流
    byte_io = BytesIO()
    resized_image.save(byte_io, format='PNG')
    image_bytes = byte_io.getvalue()
    return image_bytes

def log(level, info_text):
    print(f"[ {level} ] - {time.strftime('%Y%m%d_%H:%M:%S', time.localtime())} - {info_text}")

class Generator:
    def __init__(self, user_id, password, token) -> None:
        # _, self.token = login(user_id, password)
        self.token = token
        self.user_id = user_id
        self.password = password
        self.task_uuid = None
        self.processed_image = None
        
    def preprocess(self, prompt, image_path, processed_image , task_uuid=""):
        if processed_image and prompt and task_uuid != "":
            log("INFO", "Using cached image and prompt...")
            return prompt, processed_image
        log("INFO", "Preprocessing image...")
        success = False
        while not success:
            image_file = load_image(image_path)
            log("INFO", "Image loaded, processing...")
            if prompt and task_uuid:
                preprocess_response = rodin_preprocess_image(generate_prompt=False, image=image_file, name="images.png", token=self.token)
            else:
                preprocess_response = rodin_preprocess_image(generate_prompt=True, image=image_file, name="images.png", token=self.token)
            log("INFO", f"Image preprocessed: {preprocess_response.get('statusCode')}")
            if 'error' in preprocess_response:
                log("ERROR", f"Error in image preprocessing: {preprocess_response['error']}")
                raise RuntimeError
            elif preprocess_response.get("statusCode") == 401:
                log("WARNING", "Token expired. Logging in again...")
                _, self.token = login(self.user_id, self.password)
                continue
            else:
                try:
                    if not (prompt and task_uuid):
                        prompt = preprocess_response.get('prompt', None)   
                    processed_image = "data:image/png;base64," + preprocess_response.get('processed_image', None)
                    success = True
                except Exception as e:
                    log("ERROR", f"Error in image preprocessing: {preprocess_response}")
                    raise e

        return prompt, processed_image
    
    def generate_mesh(self, prompt, processed_image, task_uuid=""):
        log("INFO", "Generating mesh...")
        if task_uuid == "":
            settings = {'view_weights': [1]}  # Define weights as per your requirements, for multiple images, use multiple values, e,g [0.5, 0.5]
            images = [processed_image]  # List of images, all the images should be processed first
            
            mesh_response = rodin_mesh(prompt=prompt, group_uuid=None, settings=settings, images=images, name="images.jpeg", token=self.token)
            progress_checker = JobStatusChecker(BASE_URL, mesh_response['job']['subscription_key'])
            try:
                progress_checker.start()
            except Exception as e:
                log("ERROR", f"Error in generating mesh: {e}")
                time.sleep(5)
                            
            task_uuid = mesh_response['uuid'] # The task_uuid should be same during whole generation process
        else:
            new_prompt = prompt
            settings = {
                "view_weights": [1],
                "seed": random.randint(0, 10000), # Customize your seed here
                "escore": 5.5, # Temprature
            }

            update_response = rodin_update(new_prompt, task_uuid, self.token, settings)

            # Check progress
            subscription_key = update_response['job']['subscription_key']
            checker = JobStatusChecker(BASE_URL, subscription_key)
            try:
                checker.start()
            except Exception as e:
                log("ERROR", f"Error in updating mesh: {e}")
                time.sleep(5)

        history = rodin_history(task_uuid, self.token)
        try:
            preview_image = next(reversed(history.items()))[1]["preview_image"]
        except Exception as e:
            print(history)
            raise e
        response = requests.get(preview_image, stream=True)
        if response.status_code == 200:
            # 创建一个PIL Image对象
            image = Image.open(response.raw)
            # 在这里对image对象进行处理，如显示、保存等
        else:
            log("ERROR", f"Error in generating mesh: {response}")
            raise RuntimeError
        response.close()
        return image, task_uuid, crop_image(image, DEFAULT)


class JobStatusChecker:
    def __init__(self, base_url, subscription_key):
        self.base_url = base_url
        self.subscription_key = subscription_key
        self.sio = socketio.Client(logger=True, engineio_logger=True)

        @self.sio.event
        def connect():
            print("Connected to the server.")

        @self.sio.event
        def disconnect():
            print("Disconnected from server.")

        @self.sio.on('message', namespace='*')
        def message(*args, **kwargs):
            if len(args) > 2:
                data = args[2]
                if data.get('jobStatus') == 'Succeeded':
                    print("Job Succeeded! Please find the SDF image in history")
                    self.sio.disconnect()
            else:
                print("Received event with insufficient arguments.")

    def start(self):
        self.sio.connect(f"{self.base_url}/scheduler_socket?subscription={self.subscription_key}", 
                         namespaces=['/api/scheduler_socket'], transports='websocket')
        self.sio.wait()