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Update app.py
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app.py
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@@ -11,6 +11,7 @@ from PIL import Image
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import base64
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import random
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st.set_page_config(layout="wide",initial_sidebar_state="expanded",
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page_icon='π',page_title='Poth-Hole Detector')
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@@ -25,8 +26,8 @@ def get_random_image():
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return None
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random_image_filename = random.choice(image_filenames)
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random_image_path = os.path.join(image_directory, random_image_filename)
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return random_image_path
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def get_video_base64(video_path):
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with open(video_path, "rb") as file:
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video_bytes = file.read()
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@@ -194,54 +195,77 @@ def main():
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except Exception as e:
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st.error(f"An error occurred: {e}")
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elif sidebar_option == "Upload file":
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fileimage=st.file_uploader('Upload the file for detection π',type=['jpg'])
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st.info("If you haven't filed, our system will employ a default image for prediction π. Simply press the 'Predict' button and directly upload your file for analysis π§.")
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if st.button('Predict'):
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}
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else:
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st.info('Wait for the results...!')
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counter=1
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@@ -311,4 +335,4 @@ if __name__ == '__main__':
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main()
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import base64
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import random
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st.set_page_config(layout="wide",initial_sidebar_state="expanded",
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page_icon='π',page_title='Poth-Hole Detector')
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return None
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random_image_filename = random.choice(image_filenames)
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random_image_path = os.path.join(image_directory, random_image_filename)
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return random_image_path
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def get_video_base64(video_path):
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with open(video_path, "rb") as file:
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video_bytes = file.read()
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except Exception as e:
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st.error(f"An error occurred: {e}")
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elif sidebar_option == "Upload file":
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fileimage=st.file_uploader('Upload the file for detection π',type=['jpg','jpeg','png'])
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st.info("If you haven't filed, our system will employ a default image for prediction π. Simply press the 'Predict' button and directly upload your file for analysis π§.")
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if st.button('Predict'):
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if True:
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if fileimage is None:
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default_image=get_random_image()
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st.warning('β οΈ We are using random image from our backend!.')
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st.info('Wait for the results...!')
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counter=1
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pic=Image.open(default_image)
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image_np = np.array(pic)
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names={0:'POTH_HOLE'
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}
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mod1=YOLO('best.pt')
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mod1.predict(image_np,save=True,save_txt=True)
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txt_files_exist = any(filename.endswith('.txt') for filename in os.listdir('runs/detect/predict/labels'))
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if txt_files_exist:
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lis=open('runs/detect/predict/labels/image0.txt','r').readlines()
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with st.spinner('Wait for the results...!'):
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time.sleep(5)
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for line in lis:
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process_line(line, image_np,counter)
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counter+=1
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col1,col2=st.columns(2)
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with col1:
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st.info('Original Image!')
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st.image(default_image,use_column_width=True)
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with col2:
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st.info('Detected Image!')
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st.image(image_np,use_column_width=True)
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st.balloons()
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try:
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if os.path.exists('runs'):
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shutil.rmtree('runs')
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st.session_state.original_image = None # Clear the original_image variable
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except Exception as e:
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st.error(f"An error occurred: {e}")
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else:
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st.warning('β οΈPlease check your image')
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st.info("π·β¨ **Encountering the 'Please check your image' error?**")
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st.write(
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"""
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Our algorithm may not have been able to predict the content of your image. To improve results, consider the following:
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π **Verify image quality and resolution.**
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π **Ensure the image is clear and well-lit.**
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π **Check if the image meets our specified format requirements.**
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π **Consider alternative images for better results.**
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Our aim is to provide accurate predictions, and addressing these aspects can make a significant difference. If the issue persists, please reach out to our support team. We're here to help! π€π§
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"""
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)
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try:
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if os.path.exists('runs'):
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shutil.rmtree('runs')
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st.session_state.original_image = None # Clear the original_image variable
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except Exception as e:
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st.error(f"An error occurred: {e}")
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else:
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st.info('Wait for the results...!')
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counter=1
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main()
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