Upload app.py

app.py

@@ -1,9 +1,6 @@
 import os
 os.system("pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cpu")
 os.system("pip install torch-scatter torch-sparse torch-cluster torch-spline-conv torch-geometric -f https://data.pyg.org/whl/torch-1.12.0+cpu.html")
-# os.system("apt-get install -y graphviz-dev")
-# os.system("pip install pygraphviz")
-
 import gradio as gr
 from glycowork.ml.processing import dataset_to_dataloader
 import numpy as np
@@ -12,6 +9,9 @@ import torch.nn as nn
 from glycowork.motif.graph import glycan_to_nxGraph
 import networkx as nx
 import matplotlib.pyplot as plt
+from networkx.drawing.nx_agraph import write_dot
+import pygraphviz as pgv
+
 
 class EnsembleModel(nn.Module):
     def __init__(self, models):
@@ -44,8 +44,10 @@ def fn(glycan, model):
     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")
+    write_dot(graph, "graph.dot")
+    graph=pgv.AGraph("graph.dot")  
+    graph.layout(prog='dot')
+    graph.draw("graph.png")
     # Perform inference
     if model == "No data augmentation":
       model_pred = model1