convert image to pil

app.py

@@ -10,6 +10,7 @@ import torch
 import subprocess
 from groq import Groq
 import base64
+from io import BytesIO
 import os
 
 login(token=os.environ.get("HF_API_KEY"))
@@ -41,9 +42,15 @@ pipe.set_adapters(["flat", "canny"], adapter_weights=[0.7, 0.7])
 MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = 1024
 
-def encode_image(image_path):
-  with open(image_path, "rb") as image_file:
-    return base64.b64encode(image_file.read()).decode('utf-8')
+# def encode_image(image_path):
+#   with open(image_path, "rb") as image_file:
+#     return base64.b64encode(image_file.read()).decode('utf-8')
+
+def encode_image(pil_image):
+    # Convert PIL image to bytes
+    buffered = BytesIO()
+    pil_image.save(buffered, format=pil_image.format or "PNG")
+    return base64.b64encode(buffered.getvalue()).decode('utf-8')
 
 
 # @spaces.GPU #[uncomment to use ZeroGPU]
@@ -152,7 +159,7 @@ with gr.Blocks(css=css, theme=gr.themes.Soft()) as demo:
         with gr.Column(elem_id="col-container"):
             generate_button = gr.Button("Generate flat sketch", scale=0, variant="primary", elem_classes="btn btn-primary")
 
-            result = gr.Image(label="Result", show_label=False)
+            result = gr.Image(label="Result", show_label=False, type="pil")
 
             if result:
                 gr.Markdown("## Description of the garment:")