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| import fal_client | |
| from src.utils import numpy_to_base64 | |
| from src.helpers import resize_image | |
| from src.deepl import detect_and_translate | |
| def fal_ipadapter_api(input_image,ip_image,seg_prompt): | |
| #print(input_image,ip_image,seg_prompt) | |
| handler = fal_client.submit( | |
| "comfy/JarvisSan22/cloth_ipadapter", | |
| arguments={ | |
| "loadimage_1":numpy_to_base64(input_image), | |
| "loadimage_2":numpy_to_base64(ip_image), | |
| "groundingdinosamsegment (segment anything)_prompt":detect_and_translate(seg_prompt) | |
| }, | |
| ) | |
| #print(handler) | |
| result= handler.get() | |
| #image_urls=[] | |
| #print(result["outputs"]) | |
| """ | |
| for k,item in result["outputs"].items(): | |
| if "images" in item: | |
| image_urls.append(item["images"][0]["url"]) | |
| print(image_urls) | |
| return image_urls | |
| """ | |
| #print(result) | |
| return result["outputs"]["20"]["images"][0]["url"] | |
| def fal_faceswap_api(input_image,face_image): | |
| #print(input_image.shape,face_image.shape,type(face_image)) | |
| #face_image.resize((1024, 1024)) | |
| input_image=resize_image(input_image) | |
| face_image=resize_image(face_image) | |
| #print(input_image.shape,face_image.shape) | |
| handler = fal_client.submit( | |
| "fal-ai/face-swap", | |
| arguments={ | |
| "base_image_url": numpy_to_base64(input_image), | |
| "swap_image_url": numpy_to_base64(face_image), | |
| }, | |
| ) | |
| result = handler.get() | |
| #print(result) | |
| return result["image"]["url"] |