Update paths to avoid conflicts in Hub

Author: ranftlr

README.md

@@ -13,7 +13,7 @@ The pre-trained model corresponds to `DS 4` with multi-objective optimization en
 
 ### Setup 
 
-1) Download the model weights [model.pt](https://github.com/intel-isl/MiDaS/releases/download/v2/model.pt) and place the
+1) Download the model weights [model-f45da743.pt](https://github.com/intel-isl/MiDaS/releases/download/v2/model-f46da743.pt) and place the
 file in the root folder.
 
 2) Set up dependencies: 

hubconf.py

@@ -1,8 +1,9 @@
-dependencies = ['torch']
+dependencies = ["torch"]
 
 import torch
 
-from models.midas_net import MidasNet
+from midas.midas_net import MidasNet
+
 
 def MiDaS(pretrained=True, **kwargs):
     """ # This docstring shows up in hub.help()
@@ -13,8 +14,12 @@ def MiDaS(pretrained=True, **kwargs):
     model = MidasNet()
 
     if pretrained:
-        checkpoint = "https://github.com/intel-isl/MiDaS/releases/download/v2/model.pt"
-        state_dict = torch.hub.load_state_dict_from_url(checkpoint, progress=True)
+        checkpoint = (
+            "https://github.com/intel-isl/MiDaS/releases/download/v2/model-f46da743.pt"
+        )
+        state_dict = torch.hub.load_state_dict_from_url(
+            checkpoint, progress=True, check_hash=True
+        )
         model.load_state_dict(state_dict)
 
     return model

models/base_model.py midas/base_model.pymodels/base_model.py renamed to midas/base_model.py

@@ -1,5 +1,4 @@
 import torch
-import torch.nn as nn
 
 
 class BaseModel(torch.nn.Module):

models/blocks.py midas/blocks.pymodels/blocks.py renamed to midas/blocks.py

@@ -5,8 +5,8 @@
 import torch
 import torch.nn as nn
 
-from models.base_model import BaseModel
-from models.blocks import FeatureFusionBlock, Interpolate, _make_encoder
+from .base_model import BaseModel
+from .blocks import FeatureFusionBlock, Interpolate, _make_encoder
 
 
 class MidasNet(BaseModel):

models/midas_net.py midas/midas_net.pymodels/midas_net.py renamed to midas/midas_net.py

@@ -7,8 +7,8 @@
 import cv2
 
 from torchvision.transforms import Compose
-from models.midas_net import MidasNet
-from models.transforms import Resize, NormalizeImage, PrepareForNet
+from midas.midas_net import MidasNet
+from midas.transforms import Resize, NormalizeImage, PrepareForNet
 
 
 def run(input_path, output_path, model_path):
@@ -95,7 +95,7 @@ def run(input_path, output_path, model_path):
     INPUT_PATH = "input"
     OUTPUT_PATH = "output"
     # MODEL_PATH = "model.pt"
-    MODEL_PATH = "model.pt"
+    MODEL_PATH = "model-f46da743.pt"
 
     # set torch options
     torch.backends.cudnn.enabled = True