feat(model_registry): update focoos version and latency metrics and fix stdc config

Author: CuriousDolphin

focoos/model_registry/fai-cls-m-coco.json

@@ -376,7 +376,38 @@
         "classification/Recall-zebra": 95.2941
     },
     "focoos_version": "0.20.2",
-    "latency": [],
+    "latency": [
+        {
+            "fps": 588,
+            "engine": "torchscript",
+            "min": 1.568,
+            "max": 2.098,
+            "mean": 1.699,
+            "std": 0.096,
+            "im_size": 224,
+            "device": "Tesla T4"
+        },
+        {
+            "fps": 568,
+            "engine": "onnx.CUDAExecutionProvider",
+            "min": 1.733,
+            "max": 1.834,
+            "mean": 1.76,
+            "std": 0.021,
+            "im_size": 224,
+            "device": "Tesla T4"
+        },
+        {
+            "fps": 1332,
+            "engine": "onnx.TensorrtExecutionProvider",
+            "min": 0.739,
+            "max": 0.784,
+            "mean": 0.75,
+            "std": 0.01,
+            "im_size": 224,
+            "device": "Tesla T4"
+        }
+    ],
     "training_info": null,
     "updated_at": null
 }

focoos/model_registry/fai-cls-n-coco.json

@@ -375,7 +375,29 @@
         "classification/Recall-zebra": 91.76470947265625
     },
     "focoos_version": "0.20.2",
-    "latency": [],
+    "latency": [
+        {
+            "fps": 851,
+            "engine": "torchscript",
+            "min": 1.051,
+            "max": 1.824,
+            "mean": 1.175,
+            "std": 0.146,
+            "im_size": 224,
+            "device": "Tesla T4"
+        },
+        {
+            "fps": 1225,
+            "engine": "onnx.CUDAExecutionProvider",
+            "min": 0.789,
+            "max": 1.072,
+            "mean": 0.816,
+            "std": 0.044,
+            "im_size": 224,
+            "device": "Tesla T4"
+        },
+        {"fps": 2170, "engine": "onnx.TensorrtExecutionProvider", "min": 0.444, "max": 0.627, "mean": 0.461, "std": 0.029, "im_size": 224, "device": "Tesla T4"}
+    ],
     "training_info": null,
     "updated_at": null
 }

focoos/model_registry/fai-cls-s-coco.json

@@ -375,7 +375,38 @@
         "classification/Recall-zebra": 91.7647
     },
     "focoos_version": "0.20.2",
-    "latency": [],
+    "latency": [
+        {
+            "fps": 860,
+            "engine": "torchscript",
+            "min": 1.091,
+            "max": 1.3,
+            "mean": 1.163,
+            "std": 0.047,
+            "im_size": 224,
+            "device": "Tesla T4"
+        },
+        {
+            "fps": 932,
+            "engine": "onnx.CUDAExecutionProvider",
+            "min": 1.034,
+            "max": 1.303,
+            "mean": 1.072,
+            "std": 0.038,
+            "im_size": 224,
+            "device": "Tesla T4"
+        },
+        {
+            "fps": 1819,
+            "engine": "onnx.TensorrtExecutionProvider",
+            "min": 0.53,
+            "max": 0.606,
+            "mean": 0.549,
+            "std": 0.017,
+            "im_size": 224,
+            "device": "Tesla T4"
+        }
+    ],
     "training_info": null,
     "updated_at": null
 }

focoos/nn/backbone/stdc.py

@@ -189,27 +189,46 @@ class STDCConfig(BackboneConfig):
 class STDC(BaseBackbone):
     def __init__(self, config: STDCConfig):
         super().__init__(config)
-
-        if config.size == "small":
-            config.backbone_url = "https://public.focoos.ai/pretrained_models/backbones/stdc_small.pth"
-            layers = [2, 2, 2]
-            base = 64
-            block_num = 4
-            block_type = "cat"
-        elif config.size == "large":
-            config.backbone_url = "https://public.focoos.ai/pretrained_models/backbones/stdc_large.pth"
-            layers = [4, 5, 3]
-            base = 64
-            block_num = 4
-            block_type = "cat"
-        elif config.size == "nano":
-            config.backbone_url = "https://public.focoos.ai/pretrained_models/backbones/stdc_small.pth"
-            layers = [2, 2, 2]
-            base = 32
-            block_num = 4
-            block_type = "cat"
+        if config.size is not None:
+            if config.size == "small":
+                config.backbone_url = "https://public.focoos.ai/pretrained_models/backbones/stdc_small.pth"
+                layers = [2, 2, 2]
+                base = 64
+                block_num = 4
+                block_type = "cat"
+            elif config.size == "large":
+                config.backbone_url = "https://public.focoos.ai/pretrained_models/backbones/stdc_large.pth"
+                layers = [4, 5, 3]
+                base = 64
+                block_num = 4
+                block_type = "cat"
+            elif config.size == "nano":
+                config.backbone_url = "https://public.focoos.ai/pretrained_models/backbones/stdc_nano.pth"
+                layers = [2, 2, 2]
+                base = 32
+                block_num = 4
+                block_type = "cat"
+            else:
+                raise ValueError(f"Invalid size: {config.size}. The size should be small, large or nano.")
+            if config.layers and layers != config.layers:
+                logger.warning(f"Layers must be {layers} if size is {config.size}, provided {config.layers} not used.")
+            if config.base and base != config.base:
+                logger.warning(f"Base must be {base} if size is {config.size}, provided {config.base} not used.")
+            if config.block_num and block_num != config.block_num:
+                logger.warning(
+                    f"Block num must be {block_num} if size is {config.size}, provided {config.block_num} not used."
+                )
+            if config.block_type and block_type != config.block_type:
+                logger.warning(
+                    f"Block type must be {block_type} if size is {config.size}, provided {config.block_type} not used."
+                )
         else:
-            raise ValueError(f"Invalid size: {config.size}. The size should be small, large or nano.")
+            if not config.layers or not config.base or not config.block_num or not config.block_type:
+                raise ValueError("Layers, base, block_num and block_type must be provided if size is not provided.")
+            layers = config.layers
+            base = config.base
+            block_num = config.block_num
+            block_type = config.block_type
 
         if block_type == "cat":
             block = CatBottleneck

tests/test_backbone.py

@@ -6,9 +6,16 @@
 from focoos.nn.backbone.build import load_backbone
 
 # List of all backbone types with their minimum required config
+
+stdc_configs_size = [
+    {"model_type": "stdc", "use_pretrained": True, "size": size} for size in ["nano", "small", "large"]
+]
+stdc_configs_base = [
+    {"model_type": "stdc", "use_pretrained": True, "base": 64, "layers": [2, 2, 2], "block_num": 4, "block_type": "cat"}
+]
 BACKBONE_CONFIGS = {
     "resnet": [{"model_type": "resnet", "use_pretrained": False, "depth": 18}],
-    "stdc": [{"model_type": "stdc", "use_pretrained": False, "base": 64, "layers": [4, 5, 3]}],
+    "stdc": stdc_configs_size + stdc_configs_base,
     "swin": [{"model_type": "swin", "use_pretrained": False}],
     "mobilenet_v2": [{"model_type": "mobilenet_v2", "use_pretrained": False}],
     "convnextv2": [{"model_type": "convnextv2", "use_pretrained": False}],