perf: move tensor in gpu

app.py

@@ -9,6 +9,8 @@ from src.detection.graph_utils import add_bbox
 from src.detection.vision import presets
 logging.getLogger('PIL').setLevel(logging.CRITICAL)
 
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+
 
 def load_model(baseline: bool = False):
     if baseline:
@@ -21,7 +23,6 @@ def load_model(baseline: bool = False):
         checkpoint = torch.load(
             "model_split_3_FT_MOT17.pth", map_location="cpu")
         model.load_state_dict(checkpoint["model"])
-    device = torch.device('cuda:0')
     model.to(device)
     model.eval()
     return model
@@ -31,6 +32,7 @@ def frcnn_motsynth(image):
     model = load_model(baseline=True)
     transformEval = presets.DetectionPresetEval()
     image_tensor = transformEval(image, None)[0]
+    image_tensor = image_tensor.to(device)
     prediction = model([image_tensor])[0]
     image_w_bbox = add_bbox(image_tensor, prediction, 0.80)
     torchvision.io.write_png(image_w_bbox, "custom_out.png")
@@ -41,6 +43,7 @@ def frcnn_coco(image):
     model = load_model(baseline=True)
     transformEval = presets.DetectionPresetEval()
     image_tensor = transformEval(image, None)[0]
+    image_tensor = image_tensor.to(device)
     prediction = model([image_tensor])[0]
     image_w_bbox = add_bbox(image_tensor, prediction, 0.80)
     torchvision.io.write_png(image_w_bbox, "baseline_out.png")
@@ -49,7 +52,8 @@ def frcnn_coco(image):
 
 title = "Domain shift adaption on pedestrian detection with Faster R-CNN"
 description = "![alt text](http://www.aiacademy.unimore.it/media/news/ai-logo-white_2ND_EDITION.png)"
-examples = "input_examples"
+examples = ["001.jpg", "002.jpg", "003.jpg",
+            "004.jpg", "005.jpg", "006.jpg", "007.jpg", ]
 
 io_baseline = gr.Interface(frcnn_coco, gr.Image(type="pil"), gr.Image(
     type="file", shape=(1920, 1080), label="Baseline Model trained on COCO + FT on MOT17"))
@@ -58,4 +62,4 @@ io_custom = gr.Interface(frcnn_motsynth, gr.Image(type="pil"), gr.Image(
     type="file", shape=(1920, 1080), label="Faster R-CNN trained on MOTSynth + FT on MOT17"))
 
 gr.Parallel(io_baseline, io_custom, title=title,
-            description=description, examples=examples,theme="huggingface").launch(enable_queue=True)
+            description=description, examples=examples, theme="default").launch(enable_queue=True)

input_examples/log.csv

@@ -1,7 +0,0 @@
-"001.jpg"
-"002.jpg"
-"003.jpg"
-"004.jpg"
-"005.jpg"
-"006.jpg"
-"007.jpg"