Commita2abbe6

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I was so foolish, made a mistake in their loss eq

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Lines changed: 3 additions & 7 deletions

Original file line number	Diff line number	Diff line change
`@@ -162,7 +162,7 @@ def match_loss(image_a_pred, image_b_pred, matches_a, matches_b):`
`162`	`162`	`matches_a_descriptors=matches_a_descriptors.unsqueeze(0)`
`163`	`163`	`matches_b_descriptors=matches_b_descriptors.unsqueeze(0)`
`164`	`164`
`165`		`-match_loss=torch.div(1.0,num_matches* (matches_a_descriptors-matches_b_descriptors).pow(2).sum())`
	`165`	`+match_loss=torch.div(1.0,num_matches)* (matches_a_descriptors-matches_b_descriptors).pow(2).sum()`
`166`	`166`
`167`	`167`	`returnmatch_loss,matches_a_descriptors,matches_b_descriptors`
`168`	`168`
`@@ -188,12 +188,8 @@ def non_match_descriptor_loss(image_a_pred, image_b_pred, non_matches_a, non_mat`
`188`	`188`	`:return: torch.FloatTensor with shape torch.Shape([num_non_matches])`
`189`	`189`	`:rtype:`
`190`	`190`	`"""`
`191`		`-`
`192`		`-try:`
`193`		`-non_matches_a_descriptors=torch.index_select(image_a_pred,1,non_matches_a.long()).squeeze()`
`194`		`-non_matches_b_descriptors=torch.index_select(image_b_pred,1,non_matches_b.long()).squeeze()`
`195`		`-except:`
`196`		`-importpdb;pdb.set_trace()`
	`191`	`+non_matches_a_descriptors=torch.index_select(image_a_pred,1,non_matches_a.long()).squeeze()`
	`192`	`+non_matches_b_descriptors=torch.index_select(image_b_pred,1,non_matches_b.long()).squeeze()`
`197`	`193`
`198`	`194`	`# crazily enough, if there is only one element to index_select into`
`199`	`195`	`# above, then the first dimension is collapsed down, and we end up`

Lines changed: 3 additions & 1 deletion

Original file line number	Diff line number	Diff line change
`@@ -300,7 +300,7 @@ def run(self, loss_current_iteration=0, use_pretrained=False):`
`300`	`300`	`background_non_matches_a,background_non_matches_b, \`
`301`	`301`	`blind_non_matches_a,blind_non_matches_b, \`
`302`	`302`	`metadata=data`
`303`		`-print(f"Doing iteration{i} now with data:{metadata}")`
	`303`	`+#print(f"Doing iteration {i} now with data: {metadata}")`
`304`	`304`
`305`	`305`	`if (match_type==-1).all():`
`306`	`306`	`print("\n empty data, continuing\n")`
`@@ -407,6 +407,8 @@ def run(self, loss_current_iteration=0, use_pretrained=False):`
`407`	`407`	`loss.backward()`
`408`	`408`	`optimizer.step()`
`409`	`409`
	`410`	`+print(f"LOSS:{loss.item():.4e}")`
	`411`	`+`
`410`	`412`	`#if i % 10 == 0:`
`411`	`413`	`# TPV.update(self._dataset, dcn, loss_current_iteration, now_training_object_id=metadata["object_id"])`
`412`	`414`

Lines changed: 2 additions & 2 deletions

Original file line number	Diff line number	Diff line change
`@@ -37,15 +37,15 @@`
`37`	`37`	`dataset=SpartanDataset(config=config)`
`38`	`38`
`39`	`39`	`logging_dir="trained_models/tutorials"`
`40`		`-num_iterations=10000`
	`40`	`+num_iterations=3500`
`41`	`41`	`d=3# the descriptor dimension`
`42`	`42`	`name="caterpillar_%d"%(d)`
`43`	`43`	`train_config["training"]["logging_dir_name"]=name`
`44`	`44`	`train_config["training"]["logging_dir"]=logging_dir`
`45`	`45`	`train_config["dense_correspondence_network"]["descriptor_dimension"]=d`
`46`	`46`	`train_config["training"]["num_iterations"]=num_iterations`
`47`	`47`
`48`		`-TRAIN=False`
	`48`	`+TRAIN=True`
`49`	`49`	`EVALUATE=True`
`50`	`50`
`51`	`51`

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