fix: fix path

.gitattributes

@@ -32,3 +32,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+*.jpg filter=lfs diff=lfs merge=lfs -text
+*.png filter=lfs diff=lfs merge=lfs -text

app.py

@@ -28,7 +28,7 @@ def load_model(baseline: bool = False):
 
 
 def detect_with_resnet50Model_finetuning_motsynth(image):
-    model = load_model()
+    model = load_model(baseline=True)
     transformEval = presets.DetectionPresetEval()
     image_tensor = transformEval(image, None)[0]
     prediction = model([image_tensor])[0]
@@ -48,16 +48,14 @@ def detect_with_resnet50Model_baseline(image):
 
 
 title = "Performance comparision of Faster R-CNN for people detection with syntetic data"
-description = "<p style='text-align: center'>Performance comparision of Faster R-CNN models for people detecion using MOTSynth and MOT17"
-examples = [[osp.join(MOTCHA_ROOT, "MOT17", "train",
-                      "MOT17-09-DPM", "img1", "000001.jpg")]]
-
+description = "<p style='text-align: center'>Performance comparision of Faster RCNN models for people detection using MOTSynth and MOT17"
+examples = ["example1.jpg", "example2.jpg"]
 
 io_baseline = gr.Interface(detect_with_resnet50Model_baseline, gr.Image(type="pil"), gr.Image(
-    type="file", shape=(1920, 1080), label="FasterR-CNN_Resnet50_COCO"))
+    type="file", shape=(1920, 1080), label="Baseline Faster RCNN Model pretrained on COCO dataset"))
 
 io_custom = gr.Interface(detect_with_resnet50Model_finetuning_motsynth, gr.Image(type="pil"), gr.Image(
-    type="file", shape=(1920, 1080), label="FasterR-CNN_Resnet50_FinteTuning_MOTSynth"))
+    type="file", shape=(1920, 1080), label="Faster RCNN Model pretrained on COCO dataset + FT on MOTSynth"))
 
 gr.Parallel(io_baseline, io_custom, title=title,
             description=description, examples=examples).launch(enable_queue=True)