Upload app.py

app.py

@@ -9,10 +9,9 @@ from glycowork.ml.processing import dataset_to_dataloader
 import numpy as np
 import torch
 import torch.nn as nn
-from networkx.drawing.nx_agraph import write_dot
-# import pygraphviz as pgv
-# from glycowork.motif.graph import glycan_to_nxGraph
-# import networkx as nx
+from glycowork.motif.graph import glycan_to_nxGraph
+import networkx as nx
+import matplotlib.pyplot as plt
 
 class EnsembleModel(nn.Module):
     def __init__(self, models):
@@ -41,15 +40,12 @@ model3 = torch.load("model3.pt", map_location=torch.device('cpu'))
 
 def fn(glycan, model):
     # Draw graph
-    # graph = glycan_to_nxGraph(glycan)
-    # node_labels = nx.get_node_attributes(graph, 'string_labels')
-    # labels = {i:node_labels[i] for i in range(len(graph.nodes))}
-    # graph = nx.relabel_nodes(graph, labels)
-    # write_dot(graph, "graph.dot")
-    # graph=pgv.AGraph("graph.dot")  
-    # graph.layout(prog='dot')
-    # graph.draw("graph.png")
-    
+    graph = glycan_to_nxGraph(glycan)
+    node_labels = nx.get_node_attributes(graph, 'string_labels')
+    labels = {i:node_labels[i] for i in range(len(graph.nodes))}
+    graph = nx.relabel_nodes(graph, labels)
+    nx.draw(graph, with_labels=True)
+    plt.savefig("graph.png")
     # Perform inference
     if model == "No data augmentation":
       model_pred = model1
@@ -80,13 +76,13 @@ def fn(glycan, model):
     pred = np.exp(pred)/sum(np.exp(pred)) # Softmax 
     pred = [float(x) for x in pred]
     pred = {class_list[i]:pred[i] for i in range(15)}
-    return pred
+    return "graph.png", pred
 
 
 demo = gr.Interface(
     fn=fn,
     inputs=[gr.Textbox(label="Glycan sequence"), gr.Radio(label="Model",choices=["No data augmentation", "Random node deletion", "Ensemble"])],
-    outputs=[gr.Label(num_top_classes=15, label="Prediction")],
+    outputs=[gr.Image(label="Glycan graph"), gr.Label(num_top_classes=15, label="Prediction")],
     allow_flagging=False,
     title="SweetNet demo",
     examples=[["GlcOSN(a1-4)GlcA(b1-4)GlcOSN(a1-4)GlcAOS(b1-4)GlcOSN(a1-4)GlcOSN", "No data augmentation"],