Update app.py

app.py

@@ -0,0 +1,40 @@
+import numpy as np
+import gradio as gr
+import onnxruntime as ort
+from matplotlib import pyplot as plt
+from huggingface_hub import hf_hub_download
+
+model = hf_hub_download(repo_id="matjesg/cFOS_in_HC", filename="ensemble.onnx")
+
+def create_model_for_provider(model_path, provider="CPUExecutionProvider"): 
+    options = ort.SessionOptions()
+    options.intra_op_num_threads = 1
+    options.graph_optimization_level = ort.GraphOptimizationLevel.ORT_ENABLE_ALL
+    session = ort.InferenceSession(str(model_path), options, providers=[provider])
+    session.disable_fallback()
+    return session
+
+ort_session = create_model_for_provider(model)
+
+def inference(img):
+    
+    img = img[...,:1]/255
+    
+    ort_inputs = {ort_session.get_inputs()[0].name: img.astype(np.float32)}
+
+    ort_outs = ort_session.run(None, ort_inputs)
+    
+    return ort_outs[0]*255
+
+  
+title="deepflash2"
+description="deepflash2 is a deep-learning pipeline for segmentation of ambiguous microscopic images."
+examples=[['1599.tif']]
+
+gr.Interface(inference,
+             gr.inputs.Image(type="numpy"),
+             gr.outputs.Image(),
+             title=title,
+             description=description,
+             examples=examples
+             ).launch(share=True)