Spaces:
Runtime error
Runtime error
First model version
Browse files- app.py +1 -1
- det_demo.py +0 -1
- det_model/last_checkpoint +1 -1
- maskrcnn_benchmark/utils/checkpoint.py +0 -1
app.py
CHANGED
@@ -1,6 +1,6 @@
|
|
1 |
import os
|
2 |
os.system('pip install --upgrade --no-cache-dir gdown')
|
3 |
-
os.system('gdown -O ./det_model/model_ctw.pth
|
4 |
os.system('gdown -O ./workdir.zip 1mYM_26qHUom_5NU7iutHneB_KHlLjL5y')
|
5 |
os.system('unzip workdir.zip')
|
6 |
os.system('pip install "git+https://github.com/philferriere/cocoapi.git#egg=pycocotools&subdirectory=PythonAPI"')
|
|
|
1 |
import os
|
2 |
os.system('pip install --upgrade --no-cache-dir gdown')
|
3 |
+
os.system('gdown -O ./det_model/model_ctw.pth 1Ajslu_9WisuZ2nJGzE6qbD87aK6_ozzA')
|
4 |
os.system('gdown -O ./workdir.zip 1mYM_26qHUom_5NU7iutHneB_KHlLjL5y')
|
5 |
os.system('unzip workdir.zip')
|
6 |
os.system('pip install "git+https://github.com/philferriere/cocoapi.git#egg=pycocotools&subdirectory=PythonAPI"')
|
det_demo.py
CHANGED
@@ -70,7 +70,6 @@ class DetDemo(object):
|
|
70 |
self.min_image_size = min_image_size
|
71 |
|
72 |
checkpointer = DetectronCheckpointer(cfg, self.model, save_dir=cfg.OUTPUT_DIR)
|
73 |
-
print(cfg.OUTPUT_DIR, cfg.MODEL.WEIGHT)
|
74 |
_ = checkpointer.load(cfg.MODEL.WEIGHT)
|
75 |
|
76 |
self.transforms = self.build_transform()
|
|
|
70 |
self.min_image_size = min_image_size
|
71 |
|
72 |
checkpointer = DetectronCheckpointer(cfg, self.model, save_dir=cfg.OUTPUT_DIR)
|
|
|
73 |
_ = checkpointer.load(cfg.MODEL.WEIGHT)
|
74 |
|
75 |
self.transforms = self.build_transform()
|
det_model/last_checkpoint
CHANGED
@@ -1 +1 @@
|
|
1 |
-
./
|
|
|
1 |
+
./det_model/model_ctw.pth
|
maskrcnn_benchmark/utils/checkpoint.py
CHANGED
@@ -94,7 +94,6 @@ class Checkpointer(object):
|
|
94 |
f.write(last_filename)
|
95 |
|
96 |
def _load_file(self, f):
|
97 |
-
print(f)
|
98 |
return torch.load(f, map_location=torch.device("cpu"))
|
99 |
|
100 |
def _load_model(self, checkpoint):
|
|
|
94 |
f.write(last_filename)
|
95 |
|
96 |
def _load_file(self, f):
|
|
|
97 |
return torch.load(f, map_location=torch.device("cpu"))
|
98 |
|
99 |
def _load_model(self, checkpoint):
|