dnth commited on
Commit
8c1932f
1 Parent(s): c34a6f7

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +38 -29
app.py CHANGED
@@ -33,34 +33,43 @@ for root, dirs, files in os.walk(r"sample_images/"):
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  # Populate examples in Gradio interface
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  example_images = [["sample_images/" + file] for file in files]
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  # Columns: Input Image | Label | Box | Detection Threshold
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- examples = [
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- [example_images[0], False, True, 0.5],
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- [example_images[1], True, True, 0.5],
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- [example_images[2], False, True, 0.7],
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- [example_images[3], True, True, 0.7],
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- [example_images[4], False, True, 0.5],
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- [example_images[5], False, True, 0.5],
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- [example_images[6], False, True, 0.6],
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- [example_images[7], False, True, 0.6],
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- ]
 
 
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- def show_preds(input_image, display_label, display_bbox, detection_threshold):
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- if detection_threshold == 0:
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- detection_threshold = 0.5
 
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  img = PIL.Image.fromarray(input_image, "RGB")
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- pred_dict = model_type.end2end_detect(
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- img,
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- valid_tfms,
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- model,
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- class_map=class_map,
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- detection_threshold=detection_threshold,
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- display_label=display_label,
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- display_bbox=display_bbox,
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- return_img=True,
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- font_size=16,
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- label_color="#FF59D6",
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- )
 
 
 
 
 
 
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  return pred_dict["img"], len(pred_dict["detection"]["bboxes"])
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@@ -81,10 +90,10 @@ article = "<p style='text-align: center'><a href='https://dicksonneoh.com/' targ
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  gr_interface = gr.Interface(
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  fn=show_preds,
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  inputs=[
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- "image",
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- display_chkbox_label,
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- display_chkbox_box,
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- detection_threshold_slider,
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  ],
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  outputs=outputs,
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  title="Microalgae Detector with RetinaNet",
 
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  # Populate examples in Gradio interface
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  example_images = [["sample_images/" + file] for file in files]
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  # Columns: Input Image | Label | Box | Detection Threshold
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+ #examples = [
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+ # [example_images[0], False, True, 0.5],
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+ # [example_images[1], True, True, 0.5],
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+ # [example_images[2], False, True, 0.7],
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+ # [example_images[3], True, True, 0.7],
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+ # [example_images[4], False, True, 0.5],
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+ # [example_images[5], False, True, 0.5],
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+ # [example_images[6], False, True, 0.6],
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+ # [example_images[7], False, True, 0.6],
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+ #]
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+
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+ examples = [[example_images[0], example_images[1], example_images[2], example_images[3]]]
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+ #def show_preds(input_image, display_label, display_bbox, detection_threshold):
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+ def show_preds(input_image):
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+ # if detection_threshold == 0:
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+ #detection_threshold = 0.5
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  img = PIL.Image.fromarray(input_image, "RGB")
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+
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+ pred_dict = model_type.end2end_detect(img, valid_tfms, model, class_map=class_map, detection_threshold=0.5,
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+ display_label=True, display_bbox=True, return_img=True,
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+ font_size=16, label_color="#FF59D6")
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+
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+ #pred_dict = model_type.end2end_detect(
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+ # img,
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+ # valid_tfms,
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+ # model,
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+ # class_map=class_map,
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+ # detection_threshold=detection_threshold,
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+ # display_label=display_label,
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+ # display_bbox=display_bbox,
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+ # return_img=True,
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+ # font_size=16,
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+ # label_color="#FF59D6",
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+ #)
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+
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  return pred_dict["img"], len(pred_dict["detection"]["bboxes"])
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  gr_interface = gr.Interface(
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  fn=show_preds,
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  inputs=[
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+ "image"#,
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+ #display_chkbox_label,
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+ #display_chkbox_box,
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+ #detection_threshold_slider,
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  ],
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  outputs=outputs,
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  title="Microalgae Detector with RetinaNet",