Create app.py

app.py

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+import gradio as gr
+from transformers import SamModel, SamProcessor
+from PIL import Image
+import torch
+
+# Kleineres Modell (läuft stabiler auf CPU)
+model_id = "facebook/sam-vit-base"
+processor = SamProcessor.from_pretrained(model_id)
+model = SamModel.from_pretrained(model_id)
+
+def segment_image(image):
+    # Sicherstellen, dass CPU verwendet wird
+    device = torch.device("cpu")
+    model.to(device)
+    inputs = processor(images=image, return_tensors="pt").to(device)
+
+    with torch.no_grad():
+        outputs = model(**inputs)
+
+    # Masken ausgeben
+    masks = processor.post_process_masks(
+        outputs,
+        original_sizes=[image.size[::-1]],
+        reshaped_input_sizes=[image.size[::-1]]
+    )[0]
+
+    mask_array = (masks[0][0].cpu().numpy() * 255).astype("uint8")
+    mask_image = Image.fromarray(mask_array)
+    return mask_image
+
+demo = gr.Interface(
+    fn=segment_image,
+    inputs=gr.Image(type="pil"),
+    outputs=gr.Image(type="pil"),
+    title="FishBoost Segment Anything (Meta SAM 2 Demo)",
+    description="Upload an image and get the segmented result using Meta’s SAM model (CPU compatible)."
+)
+
+demo.launch()