fixed map paths

Dockerfile

@@ -17,6 +17,13 @@ USER root
 #CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "7860"]
 
 # Set up a new user named "user" with user ID 1000
+
+
+RUN mkdir -p /maps
+WORKDIR /maps
+COPY maps/*pickle .
+
+
 RUN useradd -m -u 1000 user
 
 # Switch to the "user" user
@@ -30,7 +37,6 @@ ENV HOME=/home/user \
 WORKDIR $HOME/app
 
 
-#RUN mkdir -p /data
 #RUN chmod 777 /data
 #RUN useradd -m -u 1000 user
 #USER user

main.py

@@ -70,10 +70,10 @@ def convert_to_amber_format(pdbName):
     return pt.iterload(path+'exp.crd', top = path+'exp.top')
 
 def get_maps(mapPath):
-    residueMap = pickle.load(open(mapPath+'atoms_residue_map_generate.pickle','rb'))
-    nameMap = pickle.load(open(mapPath+'atoms_name_map_generate.pickle','rb'))
-    typeMap = pickle.load(open(mapPath+'atoms_type_map_generate.pickle','rb'))
-    elementMap = pickle.load(open(mapPath+'map_atomType_element_numbers.pickle','rb'))
+    residueMap = pickle.load(open(os.path.join(mapPath,'atoms_residue_map_generate.pickle'),'rb'))
+    nameMap = pickle.load(open(os.path.join(mapPath,'atoms_name_map_generate.pickle'),'rb'))
+    typeMap = pickle.load(open(os.path.join(mapPath,'atoms_type_map_generate.pickle'),'rb'))
+    elementMap = pickle.load(open(os.path.join(mapPath,'map_atomType_element_numbers.pickle'),'rb'))
     return residueMap, nameMap, typeMap, elementMap
 
 def get_residues_atomwise(residues):

old_main.py

@@ -1,30 +0,0 @@
-import gradio as gr
-import torch
-import requests
-from torchvision import transforms
-
-model = torch.hub.load("pytorch/vision:v0.6.0", "resnet18", pretrained=True).eval()
-response = requests.get("https://git.io/JJkYN")
-labels = response.text.split("\n")
-
-
-def predict(inp):
-    inp = transforms.ToTensor()(inp).unsqueeze(0)
-    with torch.no_grad():
-        prediction = torch.nn.functional.softmax(model(inp)[0], dim=0)
-        confidences = {labels[i]: float(prediction[i]) for i in range(1000)}
-    return confidences
-
-
-def run():
-    demo = gr.Interface(
-        fn=predict,
-        inputs=gr.inputs.Image(type="pil"),
-        outputs=gr.outputs.Label(num_top_classes=3),
-    )
-
-    demo.launch(server_name="0.0.0.0", server_port=7860)
-
-
-if __name__ == "__main__":
-    run()