Update with md5sum and half precision inference

Dockerfile

@@ -38,7 +38,7 @@ RUN pyenv install ${PYTHON_VERSION} && \
     pyenv rehash && \
     pip install --no-cache-dir -U pip setuptools wheel
 
-RUN pip install --no-cache-dir -U torch==1.13.1 torchvision==0.14.1
+RUN pip install --no-cache-dir -U torch==2.0.0 torchvision==0.15.1
 COPY --chown=1000 requirements.txt /tmp/requirements.txt
 RUN pip install --no-cache-dir -U -r /tmp/requirements.txt
 

prismer/download_checkpoints.py

@@ -30,7 +30,7 @@ _MODELS = [
     "pretrain_prismerz_large",
 ]
 
-_REPO_ID = "lorenmt/prismer"
+_REPO_ID = "shikunl/prismer"
 
 
 def download_checkpoints(

prismer/experts/depth/generate_dataset.py

@@ -17,7 +17,7 @@ class Dataset(Dataset):
     def __init__(self, config, transform):
         self.data_path = config['data_path']
         self.transform = transform
-        self.data_list = [f'helpers/images/{config["im_name"]}.jpg']
+        self.data_list = [f'prismer/helpers/images/{config["im_name"]}.jpg']
 
     def __len__(self):
         return len(self.data_list)

prismer/experts/edge/generate_dataset.py

@@ -17,7 +17,7 @@ class Dataset(Dataset):
     def __init__(self, config, transform):
         self.data_path = config['data_path']
         self.transform = transform
-        self.data_list = [f'helpers/images/{config["im_name"]}.jpg']
+        self.data_list = [f'prismer/helpers/images/{config["im_name"]}.jpg']
 
     def __len__(self):
         return len(self.data_list)

prismer/experts/normal/generate_dataset.py

@@ -17,7 +17,7 @@ class CustomDataset(Dataset):
     def __init__(self, config, transform):
         self.data_path = config['data_path']
         self.transform = transform
-        self.data_list = [f'helpers/images/{config["im_name"]}.jpg']
+        self.data_list = [f'prismer/helpers/images/{config["im_name"]}.jpg']
 
     def __len__(self):
         return len(self.data_list)

prismer/experts/obj_detection/generate_dataset.py

@@ -20,7 +20,7 @@ class Dataset(Dataset):
         self.data_path = config['data_path']
         self.depth_path = os.path.join(config['save_path'], 'depth', self.data_path.split('/')[-1])
         self.transform = transform
-        self.data_list = [f'helpers/images/{config["im_name"]}.jpg']
+        self.data_list = [f'prismer/helpers/images/{config["im_name"]}.jpg']
 
     def __len__(self):
         return len(self.data_list)

prismer/experts/ocr_detection/generate_dataset.py

@@ -17,7 +17,7 @@ class Dataset(Dataset):
     def __init__(self, config, transform):
         self.data_path = config['data_path']
         self.transform = transform
-        self.data_list = [f'helpers/images/{config["im_name"]}.jpg']
+        self.data_list = [f'prismer/helpers/images/{config["im_name"]}.jpg']
 
     def __len__(self):
         return len(self.data_list)

prismer/experts/segmentation/generate_dataset.py

@@ -19,7 +19,7 @@ class Dataset(Dataset):
     def __init__(self, config, transform):
         self.data_path = config['data_path']
         self.transform = transform
-        self.data_list = [f'helpers/images/{config["im_name"]}.jpg']
+        self.data_list = [f'prismer/helpers/images/{config["im_name"]}.jpg']
 
     def __len__(self):
         return len(self.data_list)