AkashDataScience commited on
Commit
307f432
·
1 Parent(s): dfba72c

Minor change

Browse files
Files changed (1) hide show
  1. app.py +3 -1
app.py CHANGED
@@ -3,6 +3,7 @@ import numpy as np
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  import gradio as gr
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  from PIL import Image
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  from models.common import DetectMultiBackend
 
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  from utils.plots import Annotator, colors
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  from utils.torch_utils import select_device, smart_inference_mode
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  from utils.general import check_img_size, Profile, non_max_suppression, scale_boxes
@@ -45,8 +46,9 @@ def inference(input_img, conf_thres, iou_thres):
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  seen, windows, dt = 0, [], (Profile(), Profile(), Profile())
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  with dt[0]:
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- im = torch.from_numpy(input_img).to(model.device)
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  im = im.transpose((2, 0, 1))[::-1]
 
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  im = im.half() if model.fp16 else im.float() # uint8 to fp16/32
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  im /= 255 # 0 - 255 to 0.0 - 1.0
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  if len(im.shape) == 3:
 
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  import gradio as gr
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  from PIL import Image
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  from models.common import DetectMultiBackend
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+ from utils.augmentations import letterbox
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  from utils.plots import Annotator, colors
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  from utils.torch_utils import select_device, smart_inference_mode
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  from utils.general import check_img_size, Profile, non_max_suppression, scale_boxes
 
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  seen, windows, dt = 0, [], (Profile(), Profile(), Profile())
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  with dt[0]:
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+ im = letterbox(input_img, imgsz, stride=32, auto=True)[0] # padded resize
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  im = im.transpose((2, 0, 1))[::-1]
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+ im = torch.from_numpy(input_img).to(model.device)
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  im = im.half() if model.fp16 else im.float() # uint8 to fp16/32
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  im /= 255 # 0 - 255 to 0.0 - 1.0
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  if len(im.shape) == 3: