Nadine Rueegg commited on
Commit
6cdca0e
β€’
1 Parent(s): 76ae6e9

adjust print statements and close figures

Browse files
gradio_demo/barc_demo_v6.py CHANGED
@@ -21,6 +21,7 @@ import cv2
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  from matplotlib import pyplot as plt
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  from PIL import Image
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  import random
 
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  import gradio as gr
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  import sys
@@ -120,6 +121,7 @@ def run_bbox_inference(input_image):
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  img, bbox = detect_object(model=model_bbox, img_path_or_img=input_image, confidence=0.5)
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  fig = plt.figure() # plt.figure(figsize=(20,30))
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  plt.imsave(out_path, img)
 
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  return img, bbox
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  # -------------------------------------------------------------------------------------------------------------------- #
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@@ -195,9 +197,11 @@ def run_barc_inference(input_image, bbox=None):
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  total_count = 0
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  def run_complete_inference(img_path_or_img, crop_choice):
 
 
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  global total_count
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  total_count += 1
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- print('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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  from matplotlib import pyplot as plt
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  from PIL import Image
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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 sys
 
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  img, bbox = detect_object(model=model_bbox, img_path_or_img=input_image, confidence=0.5)
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  fig = plt.figure() # plt.figure(figsize=(20,30))
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  plt.imsave(out_path, img)
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+ plt.close()
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  return img, bbox
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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):
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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):
src/stacked_hourglass/datasets/imgcropslist.py CHANGED
@@ -29,7 +29,7 @@ class ImgCrops(data.Dataset):
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  self.test_name_list = []
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  for ind in np.arange(0, len(self.image_list)):
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  self.test_name_list.append(str(ind))
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- print('len(dataset): ' + str(self.__len__()))
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  def __getitem__(self, index):
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  '''img_name = self.test_name_list[index]
 
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  self.test_name_list = []
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  for ind in np.arange(0, len(self.image_list)):
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  self.test_name_list.append(str(ind))
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+ # print('len(dataset): ' + str(self.__len__()))
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  def __getitem__(self, index):
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  '''img_name = self.test_name_list[index]