Removed "Mask Only" option

- Removed "Mask Only" option as it now shows both mask and "RemBG"-ed image

app.py

@@ -1,100 +1,104 @@
-import gradio as gr
-import os
-import cv2
-from rembg import new_session, remove
-from rembg.bg import download_models
-
-def inference(file, mask, model, x, y):
-    session = new_session(model)
-
-    output = remove(
-        file,
-        session=session,
-        **{ "sam_prompt": [{"type": "point", "data": [x, y], "label": 1}] },
-        only_mask=(mask == "Mask only")
-    )
-
-    return output
-
-title = "RemBG"
-description = "Gradio demo for **[RemBG](https://github.com/danielgatis/rembg)**. To use it, simply upload your image, select a model, click Process, and wait."
-badge = """
-    <div style="position: fixed; left: 50%; text-align: center;">
-        <a href="https://github.com/danielgatis/rembg" target="_blank" style="text-decoration: none;">
-            <img src="https://img.shields.io/badge/RemBG-Github-blue" alt="RemBG Github" />
-        </a>
-    </div>
-"""
-def get_coords(evt: gr.SelectData) -> tuple:
-    return evt.index[0], evt.index[1]
-
-def show_coords(model: str):
-    visible = model == "sam"
-    return gr.update(visible=visible), gr.update(visible=visible), gr.update(visible=visible)
-
-download_models(tuple())
-
-with gr.Blocks() as app:
-    gr.Markdown(f"# {title}")
-    gr.Markdown(description)
-
-    with gr.Row():
-        inputs = gr.Image(type="numpy", label="Input Image")
-        outputs = gr.Image(label="Output Image")
-        
-    with gr.Row():
-        mask_option = gr.Radio(
-            ["Default", "Mask only"],
-            value="Default",
-            label="Output Type"
-        )
-        model_selector = gr.Dropdown(
-            [
-                "u2net",
-                "u2netp",
-                "u2net_human_seg",
-                "u2net_cloth_seg",
-                "silueta",
-                "isnet-general-use",
-                "isnet-anime",
-                "sam",
-                "bria-rmbg",
-                "birefnet-general",
-                "birefnet-general-lite",
-                "birefnet-portrait",
-                "birefnet-dis",
-                "birefnet-hrsod",
-                "birefnet-cod",
-                "birefnet-massive",
-            ],
-            value="isnet-general-use",
-            label="Model Selection"
-        )
-
-    extra = gr.Markdown("## Click on the image to capture coordinates (for SAM model)", visible=False)
-
-    x = gr.Number(label="Mouse X Coordinate", visible=False)
-    y = gr.Number(label="Mouse Y Coordinate", visible=False)
-
-    model_selector.change(show_coords, inputs=model_selector, outputs=[x, y, extra])
-    inputs.select(get_coords, None, [x, y])
-
-
-    gr.Button("Process Image").click(
-        inference,
-        inputs=[inputs, mask_option, model_selector, x, y],
-        outputs=outputs
-    )
-
-    gr.Examples(
-        examples=[
-            ["lion.png", "Default", "u2net", None, None],
-            ["girl.jpg", "Default", "u2net", None, None],
-            ["anime-girl.jpg", "Default", "isnet-anime", None, None]
-        ],
-        inputs=[inputs, mask_option, model_selector, x, y],
-        outputs=outputs
-    )
-    gr.HTML(badge)
-
-app.launch(share=True)
+import gradio as gr
+import os
+import cv2
+import numpy as np
+from rembg import new_session, remove
+from rembg.bg import download_models
+
+def inference(file, model, x, y):
+    session = new_session(model)
+    
+    mask = remove(
+        file,
+        session=session,
+        **{ "sam_prompt": [{"type": "point", "data": [x, y], "label": 1}] },
+        only_mask=True
+    )
+
+    print("Image Done")
+    if mask.shape[:2] != file.shape[:2]:
+        mask = cv2.resize(mask, (file.shape[1], file.shape[0]), interpolation=cv2.INTER_LANCZOS4)
+        
+    image = cv2.cvtColor(file, cv2.COLOR_BGR2BGRA)
+    image[:, :, 3] = mask
+
+    return (image, mask)
+
+title = "RemBG"
+description = "Gradio demo for **[RemBG](https://github.com/danielgatis/rembg)**. To use it, simply upload your image, select a model, click Process, and wait."
+badge = """
+    <div style="position: fixed; left: 50%; text-align: center;">
+        <a href="https://github.com/danielgatis/rembg" target="_blank" style="text-decoration: none;">
+            <img src="https://img.shields.io/badge/RemBG-Github-blue" alt="RemBG Github" />
+        </a>
+    </div>
+"""
+def get_coords(evt: gr.SelectData) -> tuple:
+    return evt.index[0], evt.index[1]
+
+def show_coords(model: str):
+    visible = model == "sam"
+    return gr.update(visible=visible), gr.update(visible=visible), gr.update(visible=visible)
+
+download_models(tuple())
+
+with gr.Blocks() as app:
+    gr.Markdown(f"# {title}")
+    gr.Markdown(description)
+
+    with gr.Row():
+        inputs = gr.Image(type="numpy", label="Input Image")
+        with gr.Column():
+            output_image = gr.Image(label="Output Image")
+            output_mask = gr.Image(label="Output Mask")
+        
+    model_selector = gr.Dropdown(
+        [
+            "u2net",
+            "u2netp",
+            "u2net_human_seg",
+            "u2net_cloth_seg",
+            "silueta",
+            "isnet-general-use",
+            "isnet-anime",
+            "sam",
+            "bria-rmbg",
+            "birefnet-general",
+            "birefnet-general-lite",
+            "birefnet-portrait",
+            "birefnet-dis",
+            "birefnet-hrsod",
+            "birefnet-cod",
+            "birefnet-massive",
+        ],
+        value="isnet-general-use",
+        label="Model Selection"
+    )
+
+    extra = gr.Markdown("## Click on the image to capture coordinates (for SAM model)", visible=False)
+
+    x = gr.Number(label="Mouse X Coordinate", visible=False)
+    y = gr.Number(label="Mouse Y Coordinate", visible=False)
+
+    model_selector.change(show_coords, inputs=model_selector, outputs=[x, y, extra])
+    inputs.select(get_coords, None, [x, y])
+
+
+    gr.Button("Process Image").click(
+        inference,
+        inputs=[inputs, model_selector, x, y],
+        outputs=(output_image, output_mask)
+    )
+
+    gr.Examples(
+        examples=[
+            ["lion.png", "u2net", 100, None, None],
+            ["girl.jpg", "u2net", 100, None, None],
+            ["anime-girl.jpg", "isnet-anime", 100, None, None]
+        ],
+        inputs=[inputs, model_selector, x, y],
+        outputs=(output_image, output_mask)
+    )
+    gr.HTML(badge)
+
+app.launch(share=True)