Added trained models for Jacquard dataset

skumra · May 20, 2021 · 5356954 · 5356954
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diff --git a/.gitattributes b/.gitattributes
@@ -1,3 +1,6 @@
+.92 filter=lfs diff=lfs merge=lfs -text
+.93 filter=lfs diff=lfs merge=lfs -text
+.94 filter=lfs diff=lfs merge=lfs -text
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diff --git a/trained-models/jacquard-d-grconvnet3-drop0-ch32/arch.txt b/trained-models/jacquard-d-grconvnet3-drop0-ch32/arch.txt
@@ -0,0 +1,57 @@
+----------------------------------------------------------------
+        Layer (type)               Output Shape         Param #
+================================================================
+            Conv2d-1         [-1, 32, 224, 224]           2,624
+       BatchNorm2d-2         [-1, 32, 224, 224]              64
+            Conv2d-3         [-1, 64, 112, 112]          32,832
+       BatchNorm2d-4         [-1, 64, 112, 112]             128
+            Conv2d-5          [-1, 128, 56, 56]         131,200
+       BatchNorm2d-6          [-1, 128, 56, 56]             256
+            Conv2d-7          [-1, 128, 56, 56]         147,584
+       BatchNorm2d-8          [-1, 128, 56, 56]             256
+            Conv2d-9          [-1, 128, 56, 56]         147,584
+      BatchNorm2d-10          [-1, 128, 56, 56]             256
+    ResidualBlock-11          [-1, 128, 56, 56]               0
+           Conv2d-12          [-1, 128, 56, 56]         147,584
+      BatchNorm2d-13          [-1, 128, 56, 56]             256
+           Conv2d-14          [-1, 128, 56, 56]         147,584
+      BatchNorm2d-15          [-1, 128, 56, 56]             256
+    ResidualBlock-16          [-1, 128, 56, 56]               0
+           Conv2d-17          [-1, 128, 56, 56]         147,584
+      BatchNorm2d-18          [-1, 128, 56, 56]             256
+           Conv2d-19          [-1, 128, 56, 56]         147,584
+      BatchNorm2d-20          [-1, 128, 56, 56]             256
+    ResidualBlock-21          [-1, 128, 56, 56]               0
+           Conv2d-22          [-1, 128, 56, 56]         147,584
+      BatchNorm2d-23          [-1, 128, 56, 56]             256
+           Conv2d-24          [-1, 128, 56, 56]         147,584
+      BatchNorm2d-25          [-1, 128, 56, 56]             256
+    ResidualBlock-26          [-1, 128, 56, 56]               0
+           Conv2d-27          [-1, 128, 56, 56]         147,584
+      BatchNorm2d-28          [-1, 128, 56, 56]             256
+           Conv2d-29          [-1, 128, 56, 56]         147,584
+      BatchNorm2d-30          [-1, 128, 56, 56]             256
+    ResidualBlock-31          [-1, 128, 56, 56]               0
+  ConvTranspose2d-32         [-1, 64, 113, 113]         131,136
+      BatchNorm2d-33         [-1, 64, 113, 113]             128
+  ConvTranspose2d-34         [-1, 32, 225, 225]          32,800
+      BatchNorm2d-35         [-1, 32, 225, 225]              64
+  ConvTranspose2d-36         [-1, 32, 225, 225]          82,976
+          Dropout-37         [-1, 32, 225, 225]               0
+           Conv2d-38          [-1, 1, 224, 224]             129
+          Dropout-39         [-1, 32, 225, 225]               0
+           Conv2d-40          [-1, 1, 224, 224]             129
+          Dropout-41         [-1, 32, 225, 225]               0
+           Conv2d-42          [-1, 1, 224, 224]             129
+          Dropout-43         [-1, 32, 225, 225]               0
+           Conv2d-44          [-1, 1, 224, 224]             129
+================================================================
+Total params: 1,893,124
+Trainable params: 1,893,124
+Non-trainable params: 0
+----------------------------------------------------------------
+Input size (MB): 0.19
+Forward/backward pass size (MB): 219.96
+Params size (MB): 7.22
+Estimated Total Size (MB): 227.37
+----------------------------------------------------------------
diff --git a/trained-models/jacquard-d-grconvnet3-drop0-ch32/epoch_44_iou_0.93 b/trained-models/jacquard-d-grconvnet3-drop0-ch32/epoch_44_iou_0.93
diff --git a/trained-models/jacquard-d-grconvnet3-drop0-ch32/epoch_48_iou_0.93 b/trained-models/jacquard-d-grconvnet3-drop0-ch32/epoch_48_iou_0.93
diff --git a/trained-models/jacquard-d-grconvnet3-drop0-ch32/epoch_50_iou_0.94 b/trained-models/jacquard-d-grconvnet3-drop0-ch32/epoch_50_iou_0.94
diff --git a/trained-models/jacquard-rgbd-grconvnet3-drop0-ch32/arch.txt b/trained-models/jacquard-rgbd-grconvnet3-drop0-ch32/arch.txt
@@ -0,0 +1,53 @@
+----------------------------------------------------------------
+        Layer (type)               Output Shape         Param #
+================================================================
+            Conv2d-1         [-1, 32, 224, 224]          10,400
+       BatchNorm2d-2         [-1, 32, 224, 224]              64
+            Conv2d-3         [-1, 64, 112, 112]          32,832
+       BatchNorm2d-4         [-1, 64, 112, 112]             128
+            Conv2d-5          [-1, 128, 56, 56]         131,200
+       BatchNorm2d-6          [-1, 128, 56, 56]             256
+            Conv2d-7          [-1, 128, 56, 56]         147,584
+       BatchNorm2d-8          [-1, 128, 56, 56]             256
+            Conv2d-9          [-1, 128, 56, 56]         147,584
+      BatchNorm2d-10          [-1, 128, 56, 56]             256
+    ResidualBlock-11          [-1, 128, 56, 56]               0
+           Conv2d-12          [-1, 128, 56, 56]         147,584
+      BatchNorm2d-13          [-1, 128, 56, 56]             256
+           Conv2d-14          [-1, 128, 56, 56]         147,584
+      BatchNorm2d-15          [-1, 128, 56, 56]             256
+    ResidualBlock-16          [-1, 128, 56, 56]               0
+           Conv2d-17          [-1, 128, 56, 56]         147,584
+      BatchNorm2d-18          [-1, 128, 56, 56]             256
+           Conv2d-19          [-1, 128, 56, 56]         147,584
+      BatchNorm2d-20          [-1, 128, 56, 56]             256
+    ResidualBlock-21          [-1, 128, 56, 56]               0
+           Conv2d-22          [-1, 128, 56, 56]         147,584
+      BatchNorm2d-23          [-1, 128, 56, 56]             256
+           Conv2d-24          [-1, 128, 56, 56]         147,584
+      BatchNorm2d-25          [-1, 128, 56, 56]             256
+    ResidualBlock-26          [-1, 128, 56, 56]               0
+           Conv2d-27          [-1, 128, 56, 56]         147,584
+      BatchNorm2d-28          [-1, 128, 56, 56]             256
+           Conv2d-29          [-1, 128, 56, 56]         147,584
+      BatchNorm2d-30          [-1, 128, 56, 56]             256
+    ResidualBlock-31          [-1, 128, 56, 56]               0
+  ConvTranspose2d-32         [-1, 64, 113, 113]         131,136
+      BatchNorm2d-33         [-1, 64, 113, 113]             128
+  ConvTranspose2d-34         [-1, 32, 225, 225]          32,800
+      BatchNorm2d-35         [-1, 32, 225, 225]              64
+  ConvTranspose2d-36         [-1, 32, 225, 225]          82,976
+           Conv2d-37          [-1, 1, 224, 224]             129
+           Conv2d-38          [-1, 1, 224, 224]             129
+           Conv2d-39          [-1, 1, 224, 224]             129
+           Conv2d-40          [-1, 1, 224, 224]             129
+================================================================
+Total params: 1,900,900
+Trainable params: 1,900,900
+Non-trainable params: 0
+----------------------------------------------------------------
+Input size (MB): 0.77
+Forward/backward pass size (MB): 170.52
+Params size (MB): 7.25
+Estimated Total Size (MB): 178.53
+----------------------------------------------------------------
diff --git a/trained-models/jacquard-rgbd-grconvnet3-drop0-ch32/epoch_35_iou_0.92 b/trained-models/jacquard-rgbd-grconvnet3-drop0-ch32/epoch_35_iou_0.92
diff --git a/trained-models/jacquard-rgbd-grconvnet3-drop0-ch32/epoch_42_iou_0.93 b/trained-models/jacquard-rgbd-grconvnet3-drop0-ch32/epoch_42_iou_0.93
diff --git a/trained-models/jacquard-rgbd-grconvnet3-drop0-ch32/epoch_48_iou_0.93 b/trained-models/jacquard-rgbd-grconvnet3-drop0-ch32/epoch_48_iou_0.93