From c0c6e81c01ad2f27bea9f8babde8bbdcd00a8fd2 Mon Sep 17 00:00:00 2001
From: Starbeamrainbowlabs <sbrl@starbeamrainbowlabs.com>
Date: Thu, 12 Jan 2023 18:12:50 +0000
Subject: [PATCH] dlr predict: allow for multiple outputs

---
 aimodel/src/deeplabv3_plus_test_rainfall.py | 9 ++++++---
 1 file changed, 6 insertions(+), 3 deletions(-)

diff --git a/aimodel/src/deeplabv3_plus_test_rainfall.py b/aimodel/src/deeplabv3_plus_test_rainfall.py
index c3080c5..62e2b43 100755
--- a/aimodel/src/deeplabv3_plus_test_rainfall.py
+++ b/aimodel/src/deeplabv3_plus_test_rainfall.py
@@ -256,14 +256,16 @@ def plot_samples_matplotlib(filepath, display_list, figsize=(5, 3)):
 
 
 def plot_predictions(filepath, input_items, colormap, model):
+	i = 0
 	for input_pair in input_items:
 		prediction_mask = infer(image_tensor=input_pair[0], model=model)
 		# label_colourmap = decode_segmentation_masks(input_pair[1], colormap, 2)
 		prediction_colormap = decode_segmentation_masks(prediction_mask, colormap, 2)
 		
+		print("DEBUG:plot_predictions INFER", prediction_mask)
 		
 		plot_samples_matplotlib(
-			filepath,
+			filepath.replace("$$", i),
 			[
 				# input_tensor,
 				input_pair[1], #label_colourmap
@@ -271,6 +273,7 @@ def plot_predictions(filepath, input_items, colormap, model):
 			],
 			figsize=(18, 14)
 		)
+		i += 1
 
 def get_from_batched(dataset, count):
 	result = []
@@ -284,13 +287,13 @@ def get_from_batched(dataset, count):
 
 
 plot_predictions(
-	os.path.join(DIR_OUTPUT, "predict_train.png"),
+	os.path.join(DIR_OUTPUT, "predict_train_$$.png"),
 	get_from_batched(dataset_train, 4),
 	colormap,
 	model=model
 )
 plot_predictions(
-	os.path.join(DIR_OUTPUT, "predict_validate.png"),
+	os.path.join(DIR_OUTPUT, "predict_validate_$$.png"),
 	get_from_batched(dataset_validate, 4),
 	colormap,
 	model=model