app.py

import websocket 
import uuid
import io
import gradio as gr
import numpy as np
from PIL import Image
import random
import json
import requests
import urllib.parse

client_id = str(uuid.uuid4())

def queue_prompt(prompt):
    p = {"prompt": prompt, "client_id": client_id}
    data = json.dumps(p).encode('utf-8')
    req =  requests.post("http://{}/prompt".format(server_address), data=data)
    return req.json()

def get_image(filename, subfolder, folder_type):
    data = {"filename": filename, "subfolder": subfolder, "type": folder_type}
    url_values = urllib.parse.urlencode(data)
    with requests.get("http://{}/view?{}".format(server_address, url_values)) as response:
        return response.content

def get_history(prompt_id):
    with requests.get("http://{}/history/{}".format(server_address, prompt_id)) as response:
        return response.json()

def get_images(prompt_id):
    history = get_history(prompt_id)[prompt_id]
    output_images = {}
    for o in history['outputs']:
        for node_id in history['outputs']:
            node_output = history['outputs'][node_id]
            if 'images' in node_output:
                images_output = []
                for image in node_output['images']:
                    image_data = get_image(image['filename'], image['subfolder'], image['type'])
                    images_output.append(image_data)
            output_images[node_id] = images_output

    return output_images


"""
prompt = json.load(open('workflow_api.json'))
prompt["3"]["inputs"]["seed"] = random.randint(1, 1125899906842600)

ws = websocket.WebSocket()
ws.connect("ws://{}/ws?clientId={}".format(server_address, client_id))
images = get_images(ws, prompt)
for node_id in images:
     for image_data in images[node_id]:
         im = Image.open(io.BytesIO(image_data))
         im.show()"""

def image_mod(server_address,image_path,pr=gr.Progress()):
    def queue_prompt(prompt):
        p = {"prompt": prompt, "client_id": client_id}
        data = json.dumps(p).encode('utf-8')
        req =  requests.post("http://{}/prompt".format(server_address), data=data)
        return req.json()
    def get_image(filename, subfolder, folder_type):
        data = {"filename": filename, "subfolder": subfolder, "type": folder_type}
        url_values = urllib.parse.urlencode(data)
        with requests.get("http://{}/view?{}".format(server_address, url_values)) as response:
            return response.content
    def get_history(prompt_id):
        with requests.get("http://{}/history/{}".format(server_address, prompt_id)) as response:
            return response.json()
    def get_images(prompt_id):
        history = get_history(prompt_id)[prompt_id]
        output_images = {}
        for o in history['outputs']:
            for node_id in history['outputs']:
                node_output = history['outputs'][node_id]
                if 'images' in node_output:
                    images_output = []
                    for image in node_output['images']:
                        image_data = get_image(image['filename'], image['subfolder'], image['type'])
                        images_output.append(image_data)
                output_images[node_id] = images_output

        return output_images
    server_address = server_address
    files = {"image":open(image_path, 'rb')}
    data ={
            "overwrite":None,
            "subfolder":"",
            "type":None
          }
    response = requests.post("http://{}/upload/image".format(server_address), files=files, data=data)
    if response.status_code == 200:
        response_json = response.json()
        print("Image uploaded successfully!")
    else:
        print("Image upload failed:", response.text)
        return Image.open(image_path)
    
    prompt = json.load(open('workflow_api.json'))
    prompt["3"]["inputs"]["seed"] = random.randint(1, 1125899906842600)
    prompt["12"]["inputs"]["image"] = response.json()["name"]
    ws = websocket.WebSocket()
    ws.connect("ws://{}/ws?clientId={}".format(server_address, client_id))
    prompt_id = queue_prompt(prompt)['prompt_id']
    while True:
        out = ws.recv()
        if isinstance(out, str):
            message = json.loads(out)
            if message['type'] == 'executing':
                data = message['data']
                if data['node'] is None and data['prompt_id'] == prompt_id:
                    break
            if message['type'] == 'progress':
                data = message['data']
                pr((data['value'],data['max']))
        else:
            continue
    images = get_images(prompt_id)
    result = []
    """for node,image_data in images.items():
        im = Image.open(io.BytesIO(image_data))
        result.append(im)"""
    for node_id in images:
     for image_data in images[node_id]:
        im = Image.open(io.BytesIO(image_data))
        result.append(im)
    return result  
            
iface = gr.Interface(
    fn=image_mod,
    inputs=[gr.Textbox(label='Server Address'),gr.Image(type='filepath')],
    outputs=gr.Gallery(),
    title="Image Processor",
)

iface.queue().launch()