Create config.json

config.json

@@ -0,0 +1,63 @@
+{
+  "_id": {
+    "$oid": "652bbe8d115ff300cbd113e6"
+  },
+  "network_id": "nanodet_plus_m_x1.5_416_imx500v1_mctq_Keras",
+  "date_inserted": {
+    "$date": {
+      "$numberLong": "1697371203072"
+    }
+  },
+  "network_file": "/data/projects/swat/network_database/Tensorflow2/internal/nanodet-plus-m/nanodet-plus-m-x1.5-416_quant.keras",
+  "convpy_cli_supp": "",
+  "name": "nanodet_plus_m_x1.5_mctq",
+  "framework": "Tensorflow2",
+  "accuracy_measurements": [
+    "Top1",
+    {
+      "top1": 0.3316
+    }
+  ],
+  "background": false,
+  "dataset_id": "CocoPostprocessNANODET",
+  "preprocess": [
+    {
+      "ResizeBilinear": {
+        "name": "Resize",
+        "new_height": 416,
+        "new_width": 416
+      }
+    },
+    {
+      "RGBtoBGR": {
+        "name": "RGBtoBGR"
+      }
+    },
+    {
+      "Normalize": {
+        "name": "Normalization",
+        "mean": [
+          103.53,
+          116.28,
+          123.675
+        ],
+        "std": [
+          57.375,
+          57.12,
+          58.395
+        ]
+      }
+    }
+  ],
+  "task_type": "Object_Detection",
+  "inputs_type": [
+    "RGB"
+  ],
+  "outputs_type": [
+    "boxes",
+    "classes",
+    "scores"
+  ],
+  "sdsp_conv_cli_supp": "--no-input-persistency",
+  "quantization_type": "MCTQ"
+}