test no HF_TOKEN solution

app.py

@@ -1,10 +1,8 @@
+import random
 from typing import Tuple
 
-import os
-import requests
-import random
-import numpy as np
 import gradio as gr
+import numpy as np
 import spaces
 import torch
 from PIL import Image, ImageFilter
@@ -23,8 +21,7 @@ MAX_SEED = np.iinfo(np.int32).max
 IMAGE_SIZE = 1024
 DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
 
-HF_TOKEN = os.environ.get("HF_TOKEN", None)
-client = Client("SkalskiP/florence-sam-masking", hf_token=HF_TOKEN)
+client = Client("SkalskiP/florence-sam-masking")
 
 
 def remove_background(image: Image.Image, threshold: int = 50) -> Image.Image:
@@ -42,34 +39,34 @@ def remove_background(image: Image.Image, threshold: int = 50) -> Image.Image:
     return image
 
 
-EXAMPLES = [
-    [
-        {
-            "background": Image.open(requests.get("https://media.roboflow.com/spaces/doge-2-image.png", stream=True).raw),
-            "layers": [remove_background(Image.open(requests.get("https://media.roboflow.com/spaces/doge-2-mask-2.png", stream=True).raw))],
-            "composite": Image.open(requests.get("https://media.roboflow.com/spaces/doge-2-composite-2.png", stream=True).raw),
-        },
-        "little lion",
-        None,
-        42,
-        False,
-        0.85,
-        30
-    ],
-    [
-        {
-            "background": Image.open(requests.get("https://media.roboflow.com/spaces/doge-2-image.png", stream=True).raw),
-            "layers": [remove_background(Image.open(requests.get("https://media.roboflow.com/spaces/doge-2-mask-3.png", stream=True).raw))],
-            "composite": Image.open(requests.get("https://media.roboflow.com/spaces/doge-2-composite-3.png", stream=True).raw),
-        },
-        "tattoos",
-        None,
-        42,
-        False,
-        0.85,
-        30
-    ]
-]
+# EXAMPLES = [
+#     [
+#         {
+#             "background": Image.open(requests.get("https://media.roboflow.com/spaces/doge-2-image.png", stream=True).raw),
+#             "layers": [remove_background(Image.open(requests.get("https://media.roboflow.com/spaces/doge-2-mask-2.png", stream=True).raw))],
+#             "composite": Image.open(requests.get("https://media.roboflow.com/spaces/doge-2-composite-2.png", stream=True).raw),
+#         },
+#         "little lion",
+#         None,
+#         42,
+#         False,
+#         0.85,
+#         30
+#     ],
+#     [
+#         {
+#             "background": Image.open(requests.get("https://media.roboflow.com/spaces/doge-2-image.png", stream=True).raw),
+#             "layers": [remove_background(Image.open(requests.get("https://media.roboflow.com/spaces/doge-2-mask-3.png", stream=True).raw))],
+#             "composite": Image.open(requests.get("https://media.roboflow.com/spaces/doge-2-composite-3.png", stream=True).raw),
+#         },
+#         "tattoos",
+#         None,
+#         42,
+#         False,
+#         0.85,
+#         30
+#     ]
+# ]
 
 pipe = FluxInpaintPipeline.from_pretrained(
     "black-forest-labs/FLUX.1-schnell", torch_dtype=torch.bfloat16).to(DEVICE)
@@ -143,16 +140,16 @@ def process(
 
     mask = mask.filter(ImageFilter.GaussianBlur(radius=5))
     width, height = resize_image_dimensions(original_resolution_wh=image.size)
-    resized_image = image.resize((width, height), Image.LANCZOS)
-    resized_mask = mask.resize((width, height), Image.LANCZOS)
+    image = image.resize((width, height), Image.LANCZOS)
+    mask = mask.resize((width, height), Image.LANCZOS)
 
     if randomize_seed_checkbox:
         seed_slicer = random.randint(0, MAX_SEED)
     generator = torch.Generator().manual_seed(seed_slicer)
     result = pipe(
         prompt=inpainting_prompt_text,
-        image=resized_image,
-        mask_image=resized_mask,
+        image=image,
+        mask_image=mask,
         width=width,
         height=height,
         strength=strength_slider,
@@ -160,7 +157,7 @@ def process(
         num_inference_steps=num_inference_steps_slider
     ).images[0]
     print('INFERENCE DONE')
-    return result, resized_mask
+    return result, mask
 
 
 with gr.Blocks() as demo:
@@ -232,26 +229,26 @@ with gr.Blocks() as demo:
             with gr.Accordion("Debug", open=False):
                 output_mask_component = gr.Image(
                     type='pil', image_mode='RGB', label='Input mask', format="png")
-    with gr.Row():
-        gr.Examples(
-            fn=process,
-            examples=EXAMPLES,
-            inputs=[
-                input_image_editor_component,
-                inpainting_prompt_text_component,
-                masking_prompt_text_component,
-                seed_slicer_component,
-                randomize_seed_checkbox_component,
-                strength_slider_component,
-                num_inference_steps_slider_component
-            ],
-            outputs=[
-                output_image_component,
-                output_mask_component
-            ],
-            run_on_click=True,
-            cache_examples=True
-        )
+    # with gr.Row():
+    #     gr.Examples(
+    #         fn=process,
+    #         examples=EXAMPLES,
+    #         inputs=[
+    #             input_image_editor_component,
+    #             inpainting_prompt_text_component,
+    #             masking_prompt_text_component,
+    #             seed_slicer_component,
+    #             randomize_seed_checkbox_component,
+    #             strength_slider_component,
+    #             num_inference_steps_slider_component
+    #         ],
+    #         outputs=[
+    #             output_image_component,
+    #             output_mask_component
+    #         ],
+    #         run_on_click=True,
+    #         cache_examples=True
+    #     )
 
     submit_button_component.click(
         fn=process,