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import fal_client | |
from src.utils import numpy_to_base64 | |
from src.helpers import resize_image | |
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":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"] |