download model, predict year

app.py

@@ -1,4 +1,7 @@
+import io
+
 import gradio as gr
+import requests
 import torch
 import torch.nn.functional as F
 import torchvision.transforms as transforms
@@ -6,7 +9,14 @@ from PIL import Image
 
 from constants import MAKES_MODELS, PRICE_BIN_LABELS, YEARS
 
-model = torch.jit.load("mobilenetv2_432000_calib.pt")
+print("downloading checkpoint...")
+data = requests.get(
+    "https://data.aqnichol.com/car-data/models/mobilenetv2_432000_calib_torchscript.pt",
+    stream=True,
+).content
+
+print("creating model...")
+model = torch.jit.load(io.BytesIO(data))
 model.eval()
 transform = transforms.Compose(
     [
@@ -18,6 +28,8 @@ transform = transforms.Compose(
     ]
 )
 
+print("done.")
+
 
 def classify(img: Image.Image):
     in_tensor = transform(img)[None]

requirements.txt

@@ -1,3 +1,4 @@
 torch
 torchvision
 Pillow
+requests