Hi Morganh,
Thank you for your help, I have updated the file and I no longer get the JSON object error. I am now receiving a different error “Unhashable type”:
COMMAND:
root@90a3793c78ae:/workspace/tlt-experiments/Experiments/DetectNet_V2/experiment0# tlt-infer detectnet_v2 -m /workspace/tlt-experiments/Experiments/DetectNet_V2/experiment0/model/model.step-5255.tlt -i /workspace/tlt-experiments/INFERENCE_TEST/inference_test_320x224 -o /workspace/tlt-experiments/Experiments/DetectNet_V2/experiment0/inference -bs 2 -cp /workspace/tlt-experiments/Experiments/DetectNet_V2/experiment0/detectnet_v2_inference_config.json -lw 3 -k <KEY_OMITTED_FOR_THIS_POST>
OUTPUT:
Using TensorFlow backend.
2020-01-13 18:00:22,589 [INFO] iva.detectnet_v2.scripts.inference: Overlain images will not be saved in the output path.
2020-01-13 18:00:22,590 [INFO] iva.detectnet_v2.inferencer.build_inferencer: Constructing inferencer
2020-01-13 18:00:22.590544: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2020-01-13 18:00:22.681393: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:998] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-01-13 18:00:22.681820: I tensorflow/compiler/xla/service/service.cc:150] XLA service 0x5b64190 executing computations on platform CUDA. Devices:
2020-01-13 18:00:22.681839: I tensorflow/compiler/xla/service/service.cc:158] StreamExecutor device (0): GeForce RTX 2070, Compute Capability 7.5
2020-01-13 18:00:22.705966: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 3696000000 Hz
2020-01-13 18:00:22.706499: I tensorflow/compiler/xla/service/service.cc:150] XLA service 0x5bcc770 executing computations on platform Host. Devices:
2020-01-13 18:00:22.706538: I tensorflow/compiler/xla/service/service.cc:158] StreamExecutor device (0): ,
2020-01-13 18:00:22.706855: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1433] Found device 0 with properties:
name: GeForce RTX 2070 major: 7 minor: 5 memoryClockRate(GHz): 1.62
pciBusID: 0000:01:00.0
totalMemory: 7.79GiB freeMemory: 7.07GiB
2020-01-13 18:00:22.706869: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1512] Adding visible gpu devices: 0
2020-01-13 18:00:22.707378: I tensorflow/core/common_runtime/gpu/gpu_device.cc:984] Device interconnect StreamExecutor with strength 1 edge matrix:
2020-01-13 18:00:22.707389: I tensorflow/core/common_runtime/gpu/gpu_device.cc:990] 0
2020-01-13 18:00:22.707396: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1003] 0: N
2020-01-13 18:00:22.707484: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 6874 MB memory) → physical GPU (device: 0, name: GeForce RTX 2070, pci bus id: 0000:01:00.0, compute capability: 7.5)
2020-01-13 18:00:22,707 [INFO] iva.detectnet_v2.inferencer.tlt_inferencer: Loading model from /workspace/tlt-experiments/Experiments/DetectNet_V2/experiment0/model/model.step-5255.tlt:
WARNING:tensorflow:From /usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/op_def_library.py:263: colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.
Instructions for updating:
Colocations handled automatically by placer.
2020-01-13 18:00:22,959 [WARNING] tensorflow: From /usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/op_def_library.py:263: colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.
Instructions for updating:
Colocations handled automatically by placer.
/usr/local/lib/python2.7/dist-packages/keras/engine/saving.py:292: UserWarning: No training configuration found in save file: the model was not compiled. Compile it manually.
warnings.warn('No training configuration found in save file: ’
Layer (type) Output Shape Param #
input_1 (InputLayer) (None, 3, 224, 320) 0
model_1 (Model) multiple 11604718
Total params: 11,604,718
Trainable params: 11,427,566
Non-trainable params: 177,152
2020-01-13 18:00:25,359 [INFO] iva.detectnet_v2.scripts.inference: Initialized model
2020-01-13 18:00:25,360 [INFO] iva.detectnet_v2.scripts.inference: Commencing inference
0it [00:00, ?it/s]2020-01-13 18:00:26.660909: E tensorflow/stream_executor/cuda/cuda_driver.cc:806] failed to allocate 3.58G (3849718784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory
0it [00:01, ?it/s]
ERROR:
Traceback (most recent call last):
File “/usr/local/bin/tlt-infer”, line 10, in
sys.exit(main())
File “./common/magnet_infer.py”, line 35, in main
File “./detectnet_v2/scripts/inference.py”, line 222, in main
File “./detectnet_v2/scripts/inference.py”, line 185, in inference_wrapper_batch
File “./detectnet_v2/postprocessor/bbox_handler.py”, line 73, in bbox_preprocessing
File “./detectnet_v2/postprocessor/bbox_handler.py”, line 99, in abs_bbox_converter
File “/usr/local/lib/python2.7/dist-packages/addict/addict.py”, line 64, in getitem
if name not in self:
TypeError: unhashable type
CONTENTS OF: detectnet_v2_inference_config.json
{
“dbscan_criterion”: “IOU”,
“dbscan_eps”: {
“car0”: 0.3,
“car1”: 0.3,
“car2”: 0.3,
“car3”: 0.3,
“car4”: 0.3,
“car5”: 0.3
},
“dbscan_min_samples”: {
“car0”: 0.05,
“car1”: 0.05,
“car2”: 0.05,
“car3”: 0.05,
“car4”: 0.05,
“car5”: 0.05
},
“min_cov_to_cluster”: {
“car0”: 0.005,
“car1”: 0.005,
“car2”: 0.005,
“car3”: 0.005,
“car4”: 0.005,
“car5”: 0.005
},
“min_obj_height”: {
“car0”: 4,
“car1”: 4,
“car2”: 4,
“car3”: 4,
“car4”: 4,
“car5”: 4
},
“target_classes”: [“car0”, “car1”, “car2”, “car3”, “car4”, “car5”],
“confidence_th”: {
“car0”: 0.6,
“car1”: 0.6,
“car2”: 0.6,
“car3”: 0.6,
“car4”: 0.6,
“car5”: 0.6
},
“confidence_model”: {
“car0”: { “kind”: “aggregate_cov”},
“car1”: { “kind”: “aggregate_cov”},
“car2”: { “kind”: “aggregate_cov”},
“car3”: { “kind”: “aggregate_cov”},
“car4”: { “kind”: “aggregate_cov”},
“car5”: { “kind”: “aggregate_cov”}
},
“output_map”: {
“car0”: “car0”,
“car1”: “car1”,
“car2”: “car2”,
“car3”: “car3”,
“car4”: “car4”,
“car5”: “car5”
},
“color”: {
“car0” : “red”,
“car1” : “red”,
“car2” : “red”,
“car3”: “red”,
“car4”: “red”,
“car5”: “red”
},
“postproc_classes”: [“car0”, “car1”, “car2”, “car3”, “car4”, “car5”],
“image_height”: 224,
“image_width”: 320,
“stride”: 16
}
I’m not sure what the issue is at this point. I have tried simplifying the file, utilizing the same colors, etc. Thank you for your time and help!
Sincerely,
kwindham