Create app.py

app.py

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+from transformers import AutoImageProcessor, SuperPointForKeypointDetection
+import torch
+import matplotlib.pyplot as plt
+import uuid
+import gradio as gr
+
+
+processor = AutoImageProcessor.from_pretrained("magic-leap-community/superpoint")
+model = SuperPointForKeypointDetection.from_pretrained("magic-leap-community/superpoint")
+
+def infer(image):
+  inputs = processor(image,return_tensors="pt").to(model.device, model.dtype)
+  model_outputs = model(**inputs)
+  image_sizes = [(image.size[1], image.size[0])]
+  outputs = processor.post_process_keypoint_detection(model_outputs, image_sizes)
+  keypoints = outputs[0]["keypoints"].detach().numpy()
+  scores = outputs[0]["scores"].detach().numpy()
+  image_width, image_height = image.size
+
+  plt.axis('off')
+  plt.imshow(image)
+  plt.scatter(
+      keypoints[:, 0],
+      keypoints[:, 1],
+      s=scores * 100,
+      c='cyan',
+      alpha=0.4
+  )
+  path = "./" + uuid.uuid4().hex + ".png"
+  plt.savefig(path)
+  return path
+
+title = "## SuperPoint"
+description = "Try [SuperPoint] in this demo, foundation model for keypoint detection supported in 🤗 transformers. Simply upload an image or try the example."
+iface = gr.Interface(fn = infer, inputs = gr.Image(type="pil"),
+                     outputs = gr.Image(), examples=["./bee.jpg"])
+
+iface.launch()