Updated resnet model and added test script

.gitignore

@@ -1,6 +1,8 @@
 # Project specific
 .idea
+.DS_Store
 venv
+images
 
 # Byte-compiled / optimized / DLL files
 __pycache__/

app.py

@@ -10,7 +10,7 @@ description = """
 Upload a picture to this architectural classifier trained with fast.ai. 
 """
 article = """
-I hope to learn more about various architectural styles with this tool during my travels to Europe.
+We hope you found this useful!
 """
 
 def predict(imgpath):

architecture.pkl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:b8428f71bbb7810c7a924e00c688fb104d12e143906ba768aa7e52674783d588
-size 87675873
+oid sha256:7e1ef2cf8f7eb8ee23d05374a716f91311c826b0e38dfe103ce0b2004ef04498
+size 103094229

requirements.txt

@@ -1,2 +1,3 @@
 fastai
+gradio
 timm

test_basic_api.py

@@ -0,0 +1,15 @@
+import requests
+import base64
+import json
+
+parcels_files_url = 'https://hf.space/embed/jphwang/architectural_styles/+/api/predict'
+fname = "images/dean-village.jpg"
+encoded = base64.b64encode(open(fname, "rb").read())
+data = json.dumps(f'data:image/{fname[-3:]};base64,' + encoded.decode())
+r = requests.post(
+    url=parcels_files_url,
+    json={"data": [data]
+})
+resp = r.json()
+print(resp)
+