Nadine Rueegg commited on
Commit
0d2dc80
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1 Parent(s): bfb8d88

update description and add counter

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Files changed (1) hide show
  1. scripts/gradio_demo.py +10 -6
scripts/gradio_demo.py CHANGED
@@ -31,6 +31,7 @@ import trimesh
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  import cv2
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  import shutil
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  import random
 
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  import gradio as gr
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  import torchvision
@@ -576,8 +577,14 @@ def run_bite_inference(input_image, bbox=None, apply_ttopt=True):
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  # -------------------------------------------------------------------------------------------------------------------- #
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  def run_complete_inference(img_path_or_img, crop_choice, use_ttopt):
 
 
 
 
 
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  # depending on crop_choice: run faster r-cnn or take the input image directly
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  if crop_choice == "input image is cropped":
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  if isinstance(img_path_or_img, str):
@@ -613,9 +620,9 @@ description = '''
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  #### Description
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  This is a demo for BITE (*B*eyond Priors for *I*mproved *T*hree-{D} Dog Pose *E*stimation).
 
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  You can either submit a cropped image or choose the option to run a pretrained Faster R-CNN in order to obtain a bounding box.
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- Furthermore, you have the possibility to skip test-time optimization, which will lead to faster calculation at the cost of less accurate results.
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- Please have a look at the examples below.
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  <details>
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  <summary>More</summary>
@@ -635,14 +642,11 @@ Please have a look at the examples below.
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  #### Image Sources
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  * Stanford extra image dataset
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  * Images from google search engine
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- * https://www.dogtrainingnation.com/wp-content/uploads/2015/02/keep-dog-training-sessions-short.jpghttps://www.ktvb.com/article/news/local/dogs-can-now-be-off-leash-again-in-boises-ann-morrison-park-optimist-youth-sports-complex/277-609691113
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- * https://thumbs.dreamstime.com/b/hund-und-seine-neue-hundeh%C3%BCtte-36757551.jpg
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  * https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcRnx2sHnnLU3zy1XnJB7BvGUR9spmAh5bxTUg&usqp=CAU
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  * https://www.westend61.de/en/imageView/CAVF56467/portrait-of-dog-lying-on-floor-at-home
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- * https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcTFGxMcePtorQnSJncl6WhQfbR6VRccMq9gqA&usqp=CAU
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  #### Disclosure
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- The results shown in this demo are slightly improved compared to the ones depicted within our paper. Here, we apply a regularizer on the tail.
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  </details>
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  import cv2
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  import shutil
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  import random
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+ from datetime import datetime
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  import gradio as gr
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  import torchvision
 
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  # -------------------------------------------------------------------------------------------------------------------- #
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+ total_count = 0
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  def run_complete_inference(img_path_or_img, crop_choice, use_ttopt):
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+ now = datetime.now()
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+ dt_string = now.strftime("%d/%m/%Y %H:%M:%S")
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+ global total_count
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+ total_count += 1
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+ print(dt_string + ' total count: ' + str(total_count))
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  # depending on crop_choice: run faster r-cnn or take the input image directly
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  if crop_choice == "input image is cropped":
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  if isinstance(img_path_or_img, str):
 
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  #### Description
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  This is a demo for BITE (*B*eyond Priors for *I*mproved *T*hree-{D} Dog Pose *E*stimation).
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+ To run inference on one of the examples below, click on the desired image and push the submit button. Alternatively, you may upload one of your own images.
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  You can either submit a cropped image or choose the option to run a pretrained Faster R-CNN in order to obtain a bounding box.
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+ While we recommend enabeling test-time optimization (computation can take up to a minute), you have the possibility to skip it, which will lead to faster calculation (a few seconds) at the cost of less accurate results.
 
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  <details>
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  <summary>More</summary>
 
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  #### Image Sources
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  * Stanford extra image dataset
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  * Images from google search engine
 
 
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  * https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcRnx2sHnnLU3zy1XnJB7BvGUR9spmAh5bxTUg&usqp=CAU
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  * https://www.westend61.de/en/imageView/CAVF56467/portrait-of-dog-lying-on-floor-at-home
 
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  #### Disclosure
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+ The results shown in this demo are slightly improved compared to the ones depicted within our paper, as we apply a regularizer on the tail.
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  </details>
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