Update app.py
Browse files
app.py
CHANGED
@@ -183,7 +183,6 @@ def pdb_structure(Structure_index):
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SurfacePoitCloud_all = []
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for index in Structure_index:
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structure_folder = join(temp_path, str(index))
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os.makedirs(structure_folder, exist_ok=True)
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created_folders.append(structure_folder)
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pdb_file = join(pdb_path, f"{index}.pdb")
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if os.path.exists(pdb_file):
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@@ -206,17 +205,12 @@ def pdb_structure(Structure_index):
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return SurfacePoitCloud_all_tensor
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def ACE(file):
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if not os.path.exists(pdb_path):
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os.makedirs(pdb_path)
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else:
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shutil.rmtree(pdb_path)
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os.makedirs(pdb_path)
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# df = pd.read_csv(seq_path)
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# test_sequences = df["Seq"].tolist()
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# test_Structure_index = df["Structure_index"].tolist()
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test_sequences =
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test_Structure_index =
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test_dict = {"text":test_sequences, 'structure':test_Structure_index}
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@@ -242,7 +236,6 @@ def ACE(file):
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print("=================================Start prediction========================")
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for index, (batch, structure_fea, fingerprint) in enumerate(test_dataloader):
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batchs = {k: v for k, v in batch.items()}
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print(batchs)
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outputs = model(structure_fea, batchs, fingerprint)
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probability = outputs[0].tolist()
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print(outputs)
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@@ -265,12 +258,8 @@ def ACE(file):
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summary['Probability'] = probability_all
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summary_df = pd.DataFrame(summary)
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summary_df.to_csv('output.csv', index=False)
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out_prob = "Please download csv"
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else:
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out_text = output
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out_prob = probability
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return 'output.csv', out_text, out_prob
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iface = gr.Interface(fn=ACE,
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SurfacePoitCloud_all = []
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for index in Structure_index:
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structure_folder = join(temp_path, str(index))
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created_folders.append(structure_folder)
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pdb_file = join(pdb_path, f"{index}.pdb")
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if os.path.exists(pdb_file):
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return SurfacePoitCloud_all_tensor
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def ACE(file):
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# df = pd.read_csv(seq_path)
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# test_sequences = df["Seq"].tolist()
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# test_Structure_index = df["Structure_index"].tolist()
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test_sequences = file
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test_Structure_index = "structure_1"
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test_dict = {"text":test_sequences, 'structure':test_Structure_index}
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print("=================================Start prediction========================")
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for index, (batch, structure_fea, fingerprint) in enumerate(test_dataloader):
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batchs = {k: v for k, v in batch.items()}
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outputs = model(structure_fea, batchs, fingerprint)
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probability = outputs[0].tolist()
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print(outputs)
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summary['Probability'] = probability_all
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summary_df = pd.DataFrame(summary)
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summary_df.to_csv('output.csv', index=False)
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out_text = output
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out_prob = probability
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return 'output.csv', out_text, out_prob
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iface = gr.Interface(fn=ACE,
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