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Runtime error
Runtime error
Cleaning up App.py
Browse files
app.py
CHANGED
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@@ -1,5 +1,4 @@
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import gradio as gr
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from gradio.outputs import Label
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import cv2
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import requests
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import os
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@@ -39,7 +38,6 @@ def show_preds_image(image_path):
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outputs = model.predict(source=image_path)
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results = outputs[0].cpu().numpy()
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for i, det in enumerate(results.boxes.xyxy):
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# print(det.xyxy)
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cv2.rectangle(
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image,
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(int(det[0]), int(det[1])),
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@@ -52,8 +50,6 @@ def show_preds_image(image_path):
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inputs_image = [
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gr.components.Image(type="filepath", label="Input Image"),
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# gr.components.Video(type="filepath", label="Input Video", optional=True),
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-
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]
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outputs_image = [
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gr.components.Image(type="numpy", label="Output Image"),
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@@ -65,10 +61,8 @@ interface_image = gr.Interface(
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title="Pothole detector",
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examples=path,
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cache_examples=False,
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# live=True,
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)
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-
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def show_preds_video(video_path):
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cap = cv2.VideoCapture(video_path)
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while(cap.isOpened()):
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@@ -78,7 +72,6 @@ def show_preds_video(video_path):
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outputs = model.predict(source=frame)
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results = outputs[0].cpu().numpy()
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for i, det in enumerate(results.boxes.xyxy):
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# print(det.xyxy)
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cv2.rectangle(
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frame_copy,
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(int(det[0]), int(det[1])),
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@@ -103,9 +96,8 @@ interface_video = gr.Interface(
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title="Pothole detector",
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examples=video_path,
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cache_examples=False,
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# live=True,
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)
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gr.TabbedInterface(
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[interface_image, interface_video],
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tab_names=['Image inference', 'Video inference']
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import gradio as gr
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import cv2
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import requests
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import os
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outputs = model.predict(source=image_path)
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results = outputs[0].cpu().numpy()
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for i, det in enumerate(results.boxes.xyxy):
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cv2.rectangle(
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image,
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(int(det[0]), int(det[1])),
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inputs_image = [
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gr.components.Image(type="filepath", label="Input Image"),
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]
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outputs_image = [
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gr.components.Image(type="numpy", label="Output Image"),
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title="Pothole detector",
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examples=path,
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cache_examples=False,
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)
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def show_preds_video(video_path):
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cap = cv2.VideoCapture(video_path)
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while(cap.isOpened()):
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outputs = model.predict(source=frame)
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results = outputs[0].cpu().numpy()
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for i, det in enumerate(results.boxes.xyxy):
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cv2.rectangle(
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frame_copy,
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(int(det[0]), int(det[1])),
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title="Pothole detector",
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examples=video_path,
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cache_examples=False,
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)
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+
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gr.TabbedInterface(
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[interface_image, interface_video],
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tab_names=['Image inference', 'Video inference']
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