Encoded PIL image for FAL

app.py

@@ -8,6 +8,8 @@ import logging
 import dotenv
 import fal_client
 import requests
+import base64
+from io import BytesIO
 from typing import Dict, List, Tuple, Union, Optional
 
 # dotenv.load_dotenv()
@@ -338,27 +340,33 @@ def upload_file(img_file):
     # Return URL
     return file_path
 
+def encode_image(image):
+    buffer = BytesIO()
+    image.save(buffer, format="PNG")  # You can change to JPEG if needed
+    encoded_image = base64.b64encode(buffer.getvalue()).decode("utf-8")
+    return encoded_image
+
 def generate_ai_bg(input_img, prompt):
-    hf_input_img = upload_file(input_img)["url"]
+    hf_input_img = encode_image(input_img)
 
-    # handler = fal_client.submit(
-    #     "fal-ai/iclight-v2",
-    #     arguments={
-    #         "prompt": prompt,
-    #         "image_url": hf_input_img
-    #     },
-    #     webhook_url="https://optional.webhook.url/for/results",
-    # )
+    handler = fal_client.submit(
+        "fal-ai/iclight-v2",
+        arguments={
+            "prompt": prompt,
+            "image_url": hf_input_img
+        },
+        webhook_url="https://optional.webhook.url/for/results",
+    )
 
-    # request_id = handler.request_id
+    request_id = handler.request_id
 
-    # status = fal_client.status("fal-ai/iclight-v2", request_id, with_logs=True)
+    status = fal_client.status("fal-ai/iclight-v2", request_id, with_logs=True)
 
-    # result = fal_client.result("fal-ai/iclight-v2", request_id)
+    result = fal_client.result("fal-ai/iclight-v2", request_id)
 
-    # ic_light_img = result['images'][0]['url']
+    ic_light_img = result['images'][0]['url']
 
-    # return ic_light_img
+    return ic_light_img
 
 def generate_image(input_img, prompt):
     ai_gen_image = generate_ai_bg(input_img, prompt)