Upload fal_api.py

src/fal_api.py

@@ -0,0 +1,46 @@
+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"]