Add pick color

pages/App.py

@@ -256,7 +256,7 @@ def load_image(in_image_file):
         in_image_file (string or Streamlit UploadedFile): image to consider
 
     Returns:
-        string      : locally saved image path
+        string      : locally saved image path (img.)
         PIL.Image   : input file opened with Pillow
         matrix      : input file opened with Opencv
     """
@@ -267,9 +267,9 @@ def load_image(in_image_file):
     #    out_image_path = "img."+in_image_file.name.split('.')[-1]
 
     if isinstance(in_image_file, str):
-        out_image_path = "wrk_"+in_image_file
+        out_image_path = "tmp/wrk_"+in_image_file
     else:
-        out_image_path = "wrk_"+in_image_file.name
+        out_image_path = "tmp/wrk_"+in_image_file.name
 
     img = Image.open(in_image_file)
     img_saved = img.save(out_image_path)
@@ -778,7 +778,7 @@ def tesserocr_recog(in_img, in_params, in_nb_images):
 ###
 def draw_reco_images(in_image, in_boxes_coordinates, in_list_texts, in_list_confid, \
                      in_dict_back_colors, in_df_results_tesseract, in_reader_type_list, \
-                     in_font_scale=3, in_conf_threshold=65):
+                     in_font_scale=1, in_conf_threshold=65):
     """Draw recognized text on original image, for each OCR solution used
 
     Args:
@@ -1099,7 +1099,7 @@ Use rectlar box to calculate faster, and polygonal box more accurate for curved
                     placeholder='Limit tesseract to recognize only this characters', \
                     help='Example for numbers only : 0123456789')
 
-        color_hex = col2.color_picker('Pick a color for boxes outlines', '#004C99')
+        color_hex = col2.color_picker('Set a color for box outlines:', '#004C99')
         color_part = color_hex.lstrip('#')
         color = tuple(int(color_part[i:i+2], 16) for i in (0, 2, 4))
 
@@ -1358,7 +1358,7 @@ Use rectlar box to calculate faster, and polygonal box more accurate for curved
 
                     col_font, col_threshold = st.columns(2)
 
-                    col_font.slider('Font scale', 1, 7, 4, step=1, key="font_scale_sld")
+                    col_font.slider('Font scale', 1, 7, 1, step=1, key="font_scale_sld")
                     col_threshold.slider('% confidence threshold for text color change', 40, 100, 64, \
                                         step=1, key="conf_threshold_sld")
                     col_threshold.write("(text color is black below this % confidence threshold, \