Spaces:
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Sleeping
AlshimaaGamalAlsaied
commited on
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86567ab
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Parent(s):
b2eb80d
commit
Browse files
app.py
CHANGED
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@@ -1,6 +1,6 @@
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import gradio as gr
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#import torch
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import
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import subprocess
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import tempfile
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import time
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@@ -12,8 +12,10 @@ import gradio as gr
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# # Images
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# #torch.hub.
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# #torch.hub.download_url_to_file('https://raw.githubusercontent.com/obss/sahi/main/tests/data/small-vehicles1.jpeg', 'small-vehicles1.jpeg')
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def image_fn(
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image: gr.inputs.Image = None,
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@@ -23,7 +25,7 @@ def image_fn(
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iou_threshold: gr.inputs.Slider = 0.45,
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):
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"""
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-
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Args:
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image: Input image
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model_path: Path to the model
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Rendered image
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"""
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model =
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model.conf = conf_threshold
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model.iou = iou_threshold
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results = model([image], size=image_size)
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@@ -76,7 +78,7 @@ demo_app.launch(debug=True, enable_queue=True)
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# iou_threshold: gr.inputs.Slider = 0.45,
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# ):
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# """
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#
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# Args:
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# image: Input image
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# model_path: Path to the model
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@@ -87,7 +89,7 @@ demo_app.launch(debug=True, enable_queue=True)
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# Rendered image
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# """
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# model =
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# model.conf = conf_threshold
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# model.iou = iou_threshold
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# results = model([image], size=image_size)
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@@ -96,7 +98,7 @@ demo_app.launch(debug=True, enable_queue=True)
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# def video_fn(model_path, video_file, conf_thres, iou_thres, start_sec, duration):
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# model =
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# start_timestamp = time.strftime("%H:%M:%S", time.gmtime(start_sec))
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# end_timestamp = time.strftime("%H:%M:%S", time.gmtime(start_sec + duration))
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import gradio as gr
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#import torch
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import yolov7
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import subprocess
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import tempfile
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import time
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# # Images
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# #torch.hub.download_url_t
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# o_file('https://github.com/ultralytics/yolov5/raw/master/data/images/zidane.jpg', 'zidane.jpg')
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# #torch.hub.download_url_to_file('https://raw.githubusercontent.com/obss/sahi/main/tests/data/small-vehicles1.jpeg', 'small-vehicles1.jpeg')
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def image_fn(
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image: gr.inputs.Image = None,
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iou_threshold: gr.inputs.Slider = 0.45,
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):
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"""
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YOLOv7 inference function
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Args:
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image: Input image
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model_path: Path to the model
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Rendered image
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"""
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model = yolov7.load(model_path, device="cpu", hf_model=True, trace=False)
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model.conf = conf_threshold
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model.iou = iou_threshold
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results = model([image], size=image_size)
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# iou_threshold: gr.inputs.Slider = 0.45,
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# ):
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# """
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# YOLOv7 inference function
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# Args:
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# image: Input image
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# model_path: Path to the model
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# Rendered image
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# """
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# model = yolov7.load(model_path, device="cpu", hf_model=True, trace=False)
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# model.conf = conf_threshold
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# model.iou = iou_threshold
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# results = model([image], size=image_size)
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# def video_fn(model_path, video_file, conf_thres, iou_thres, start_sec, duration):
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# model = yolov7.load(model_path, device="cpu", hf_model=True, trace=False)
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# start_timestamp = time.strftime("%H:%M:%S", time.gmtime(start_sec))
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# end_timestamp = time.strftime("%H:%M:%S", time.gmtime(start_sec + duration))
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