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app.py

@@ -8,7 +8,6 @@ from diffusers import FluxFillPipeline
 from PIL import Image, ImageOps
 from sam2.sam2_image_predictor import SAM2ImagePredictor
 import numpy as np
-import matplotlib.pyplot as plt
 
 torch.set_float32_matmul_precision(["high", "highest"][0])
 
@@ -125,6 +124,7 @@ def rmbg(image=None, url=None):
 
 
 def mask_generation(image=None, d=None):
+    d = eval(d)  # convert this to dictionary
     predictor = SAM2ImagePredictor.from_pretrained("facebook/sam2-hiera-tiny")
     predictor.set_image(image)
     input_point = np.array(d["input_points"])
@@ -220,14 +220,14 @@ sam2_tab = gr.Interface(
     inputs=[
         gr.Number(4, interactive=False),
         gr.Image(type="pil"),
-        gr.JSON(),
+        gr.Text(),
     ],
     outputs=gr.Gallery(),
     examples=[
         [
             4,
             "./assets/truck.jpg",
-            {"input_points": [[500, 375], [1125, 625]], "input_labels": [1, 0]},
+            '{"input_points": [[500, 375], [1125, 625]], "input_labels": [1, 0]}',
         ]
     ],
     api_name="sam2",