Fixing python script for generation

applications/object_detection_torch/README.md

@@ -36,7 +36,22 @@ If resolution is updated in entity generation, it must be updated in the followi
 
 ## Building the application
 
-Please refer to the top level Holohub README.md file for information on how to build this application.
+The best way to run this application is inside the container, as it would provide all the required third-party packages:
+
+```bash
+# Create the container image for this application
+./dev_container build --docker_file applications/object_detection_torch/Dockerfile --img object_detection_torch
+# Launch the container
+./dev_container launch --img object_detection_torch
+# Build the application. Note that this downloads the video data as well
+./run build object_detection_torch
+# Generate the pytorch model
+python3 applications/object_detection_torch/generate_resnet_model.py  data/object_detection_torch/frcnn_resnet50_t.pt
+# Run the application
+./run launch object_detection_torch
+```
+
+Please refer to the top level Holohub README.md file for more information on how to build this application.
 
 ## Running the application
 

applications/object_detection_torch/generate_resnet_model.py

@@ -13,21 +13,23 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import sys
 import os
+import sys
 
 import torch
 from torchvision.models import detection
 
-os.environ['TORCH_HOME'] = os.getcwd()
+os.environ["TORCH_HOME"] = os.getcwd()
 
 model_file = "frcnn_resnet50_t.pt"
 if len(sys.argv) > 1:
     model_file = sys.argv[1]
 
 DEVICE = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
-det_model = detection.fasterrcnn_resnet50_fpn(progress=True).to(DEVICE)
+det_model = detection.fasterrcnn_resnet50_fpn(
+    pretrained=True, progress=True, weights_backbone=True
+).to(DEVICE)
 
 det_model.eval()
 det_model_script = torch.jit.script(det_model)