implement app.py; download ckpt from huggingface_hub

.gitignore

@@ -0,0 +1,5 @@
+*.ipynb
+.ipynb_checkpoints/
+flagged/
+.DS_Store
+**/.DS_Store

app.py

@@ -1,7 +1,34 @@
 import gradio as gr
 
-def greet(name):
-    return "Hello " + name + "!!"
+import os
+import glob
+import torch
+from molscribe import MolScribe
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
+from huggingface_hub import hf_hub_download
+
+REPO_ID = "yujieq/MolScribe"
+FILENAME = "swin_base_char_aux_200k.pth"
+ckpt_path = hf_hub_download(REPO_ID, FILENAME)
+
+device = torch.device('cpu')
+model = MolScribe(ckpt_path, device)
+
+def predict(image):
+    smiles, molblock = model.predict_image(image)
+    return smiles, molblock
+
+iface = gr.Interface(
+    predict,
+    inputs=gr.Image(label="Upload molecular image"),
+    outputs=[
+        gr.Textbox(label="SMILES"),
+        gr.Textbox(label="Molfile"),
+    ],
+    allow_flagging="auto",
+    title="MolScribe",
+    description="Convert a molecular image into SMILES and Molfile. Code: https://github.com/thomas0809/MolScribe",
+    examples=sorted(glob.glob('examples/*.png')),
+    examples_per_page=20,
+)
 iface.launch()

requirements.txt

@@ -0,0 +1 @@
+git+https://github.com/thomas0809/MolScribe.git#egg=MolScribe