Upload traffic structure configuration

models/mod.json

@@ -1,3 +1,3 @@
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+size 297963

models/mod.params

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models/mod.so

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models/vamc.yaml

@@ -1,30 +1,25 @@
 dataset:
-  path: det_coco_calib
-  sampler: {get_data_num: 100, suffix: null}
+  path: ILSVRC2012_img_calib
+  sampler: {get_data_num: 1000, suffix: JPEG}
   transform_ops:
   - {type: DecodeImage}
-  - adaptive_side: long
-    size: [640, -1]
+  - size: [256, 256]
     type: Resize
-  - {pad_to_square: true, type: Pad}
-  - {norm_type: null, type: Normalize}
+  - crop_size: [224, 224]
+    type: CenterCrop
+  - mean: [0.485, 0.456, 0.406]
+    std: [0.229, 0.224, 0.225]
+    type: Normalize
   - {type: ToTensor}
 engine:
-  add_extra_ops_to_graph:
-    params:
-      anchor: [3, 11, 7, 7, 6, 17, 14, 12, 9, 24, 25, 20, 32, 32, 71, 27, 81, 75]
-      confidence_threshold: 0.25
-      nms_threshold: 0.45
-      num_classes: 80
-      strides: [8, 16, 32]
-    type: yolov5_nms
-  calibration: {calibrate_mode: kl_divergence, quantize_per_channel: true, stream_mode: true}
-  common: {cluster_mode: 0, data_transport_mode: 3}
+  add_extra_ops_to_graph: {type: softmax}
+  calibration: {calibrate_mode: percentile, quantize_per_channel: true, stream_mode: true}
+  common: {cluster_mode: 0}
   dtype: int8
   type: vacc
 model:
-  checkpoint: best_299.torchscript.pt
+  checkpoint: onnx/carcolor.onnx
   inputs:
-    input: [1, 3, 640, 640]
-  name: yolov7_tiny_traffic
+    input: [1, 3, 224, 224]
+  name: carcolor
 workspace: {enable_ir: false, save_log: true, work_dir: ./deploy_weights/}