Add application file

app.py

@@ -1,20 +1,52 @@
-import matplotlib.pyplot as plt
-from PIL import Image
+import gradio as gr
+import torch
+from segment_anything import sam_model_registry, SamPredictor
 import numpy as np
+import cv2
+from PIL import Image
+
+import os
+import urllib.request
+
+MODEL_URL = "https://dl.fbaipublicfiles.com/segment_anything/sam_vit_b_01ec64.pth"
+MODEL_PATH = "sam_vit_b.pth"
+
+# Eğer model yoksa indir
+if not os.path.exists(MODEL_PATH):
+    print("Model indiriliyor...")
+    urllib.request.urlretrieve(MODEL_URL, MODEL_PATH)
+    print("Model indirildi.")
+
+# Model yükle 
+model_type = "vit_b"
+
+device = "cuda" if torch.cuda.is_available() else "cpu"
+sam = sam_model_registry[model_type](checkpoint=MODEL_PATH)
+sam.to(device=device)
+predictor = SamPredictor(sam)
+
+def segment(image, x, y):
+    image = np.array(image)
+    predictor.set_image(image)
+    input_point = np.array([[x, y]])
+    input_label = np.array([1])
+    masks, _, _ = predictor.predict(
+        point_coords=input_point,
+        point_labels=input_label,
+        multimask_output=False,
+    )
+    mask = masks[0]
+    masked_image = image.copy()
+    masked_image[~mask] = 0
+    return Image.fromarray(masked_image)
+
+with gr.Blocks() as demo:
+    with gr.Row():
+        image_input = gr.Image(type="pil")
+        x = gr.Number(label="X")
+        y = gr.Number(label="Y")
+        btn = gr.Button("Segment")
+    output = gr.Image()
+    btn.click(fn=segment, inputs=[image_input, x, y], outputs=output)
 
-def show_mask(mask, ax, random_color=False):
-    if random_color:
-        color = np.concatenate([np.random.random(3), np.array([0.6])], axis=0)
-    else:
-        color = np.array([30 / 255, 144 / 255, 255 / 255, 0.6])
-    h, w = mask.shape[-2:]
-    mask_image = mask.reshape(h, w, 1) * color.reshape(1, 1, -1)
-    ax.imshow(mask_image)
-    
-
-plt.imshow(np.array(raw_image))
-ax = plt.gca()
-for mask in outputs["masks"]:
-    show_mask(mask, ax=ax, random_color=True)
-plt.axis("off")
-plt.show()
+demo.launch(share=True)

requirements.txt

@@ -0,0 +1,6 @@
+gradio
+torch
+opencv-python
+numpy
+Pillow
+git+https://github.com/facebookresearch/segment-anything.git