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For grounded_light_hqsam using "vit_h" for sam encoder, first part takes 1.574 second and second part takes 0.611 second.
And for grounded_sam_simple_demo using "vit_tiny", first part takes 2.177 second and second part takes 0.136 second.
In my opinion, the shorter time for second part is okay because vit_tiny is light model.
But I have no idea why the first part takes more time for vit_tiny.
I want to use these model in real-time, so I want it to take a shorter time.
I would appreciate it if you could give me some advice on why this result came out and how to shorten the time.
Thank you!
The text was updated successfully, but these errors were encountered:
Hello! Thank you for your great work.
Recently, I tested several given code like "grounded_light_hqsam" and "grounded_sam_simple_demo".
And there is some weird results for following code.
(First part)
detections = grounding_dino_model.predict_with_classes(
image=image,
classes=CLASSES,
box_threshold=BOX_THRESHOLD,
text_threshold=BOX_THRESHOLD
)
(Second part)
detections.mask = segment(
sam_predictor=sam_predictor,
image=cv2.cvtColor(image, cv2.COLOR_BGR2RGB),
xyxy=detections.xyxy
)
For grounded_light_hqsam using "vit_h" for sam encoder, first part takes 1.574 second and second part takes 0.611 second.
And for grounded_sam_simple_demo using "vit_tiny", first part takes 2.177 second and second part takes 0.136 second.
In my opinion, the shorter time for second part is okay because vit_tiny is light model.
But I have no idea why the first part takes more time for vit_tiny.
I want to use these model in real-time, so I want it to take a shorter time.
I would appreciate it if you could give me some advice on why this result came out and how to shorten the time.
Thank you!
The text was updated successfully, but these errors were encountered: