FaceSwap.py

#This is an example that uses the websockets api to know when a prompt execution is done
#Once the prompt execution is done it downloads the images using the /history endpoint

import websocket #NOTE: websocket-client (https://github.com/websocket-client/websocket-client)
import uuid
import json
import urllib.request
import urllib.parse

server_address = "127.0.0.1:8188"
client_id = str(uuid.uuid4())

def queue_prompt(prompt):
    p = {"prompt": prompt, "client_id": client_id}
    data = json.dumps(p).encode('utf-8')
    req =  urllib.request.Request("http://{}/prompt".format(server_address), data=data)
    return json.loads(urllib.request.urlopen(req).read())

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

def get_history(prompt_id):
    with urllib.request.urlopen("http://{}/history/{}".format(server_address, prompt_id)) as response:
        return json.loads(response.read())

def get_images(ws, prompt):
    prompt_id = queue_prompt(prompt)['prompt_id']
    output_images = {}
    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 #Execution is done
        else:
            continue #previews are binary data

    history = get_history(prompt_id)[prompt_id]
    for node_id in history['outputs']:
        node_output = history['outputs'][node_id]
        images_output = []
        if 'images' in node_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_text = """
{
  "1": {
    "inputs": {
      "image": "/home/ml/Desktop/comfy_to_python/output.jpg",
      "upload": "image"
    },
    "class_type": "LoadImage",
    "_meta": {
      "title": "Load Image"
    }
  },
  "2": {
    "inputs": {
      "image": "/home/ml/Desktop/comfy_to_python/me.jpg",
      "upload": "image"
    },
    "class_type": "LoadImage",
    "_meta": {
      "title": "Load Image"
    }
  },
  "4": {
    "inputs": {
      "images": [      
        "5",
        0
      ]
    },
    "class_type": "PreviewImage",
    "_meta": {
      "title": "Preview Image"
    }
  },
  "5": {
    "inputs": {
      "enabled": true,
      "swap_model": "inswapper_128.onnx",
      "facedetection": "YOLOv5l",
      "face_restore_model": "none",
      "face_restore_visibility": 1,
      "codeformer_weight": 1,
      "detect_gender_input": "no",
      "detect_gender_source": "no",
      "input_faces_index": "0",
      "source_faces_index": "0",
      "console_log_level": 1,
      "input_image": [
        "1",
        0
      ],
      "source_image": [
        "2",
        0
      ]
    },
    "class_type": "ReActorFaceSwap",
    "_meta": {
      "title": "ReActor 🌌 Fast Face Swap"
    }
  }
}
"""

prompt = json.loads(prompt_text)
# #set the text prompt for our positive CLIPTextEncode
# prompt["6"]["inputs"]["text"] = "your instruction here"

prompt["1"]["inputs"]["image"] = "/home/ml/Desktop/comfy_to_python/66.jpg"
prompt["2"]["inputs"]["image"] = "/home/ml/Desktop/comfy_to_python/me.jpg"

# # If you have a group input face image change the number here (1,2,3,..) if single then put 0.
# prompt["5"]["inputs"]["input_faces_index"] = ""

# # If you have a group source face image change the number here (1,2,3,..) if single then put 0.
# prompt["5"]["inputs"]["source_faces_index"] = ""

ws = websocket.WebSocket()
ws.connect("ws://{}/ws?clientId={}".format(server_address, client_id))
images = get_images(ws, prompt)

# Commented out code to display the output images:

for node_id in images:
    for image_data in images[node_id]:
        from PIL import Image
        import io
        image = Image.open(io.BytesIO(image_data))
        image.save("output1.jpg")
        # image.show()