From 60aaeed1daece3964a22721b28353f13e4295be0 Mon Sep 17 00:00:00 2001 From: ganeshkondaka <123860055+ganeshkondaka@users.noreply.github.com> Date: Fri, 19 Apr 2024 20:37:29 +0530 Subject: [PATCH] Add files via upload --- app.py | 132 ++++++++++++++++++++++++++++++++++++++++++++++++++++++ modelh.h5 | Bin 0 -> 2966232 bytes 2 files changed, 132 insertions(+) create mode 100644 app.py create mode 100644 modelh.h5 diff --git a/app.py b/app.py new file mode 100644 index 0000000..5c334ed --- /dev/null +++ b/app.py @@ -0,0 +1,132 @@ +import os +import streamlit as st +from streamlit_option_menu import option_menu +import numpy as np +from PIL import Image +import pickle + +from IPython.display import HTML +import streamlit as st +from gtts import gTTS +from pydub import AudioSegment +from io import BytesIO + +# Dictionary mapping class indices to class names +classes = { 0:'Speed limit (20km/h)', + 1:'Speed limit (30km/h)', + 2:'Speed limit (50km/h)', + 3:'Speed limit (60km/h)', + 4:'Speed limit (70km/h)', + 5:'Speed limit (80km/h)', + 6:'End of speed limit (80km/h)', + 7:'Speed limit (100km/h)', + 8:'Speed limit (120km/h)', + 9:'No passing', + 10:'No passing veh over 3.5 tons', + 11:'Right-of-way at intersection', + 12:'Priority road', + 13:'Yield', + 14:'Stop', + 15:'No vehicles', + 16:'Vehicle > 3.5 tons prohibited', + 17:'No entry', + 18:'General caution', + 19:'Dangerous curve left', + 20:'Dangerous curve right', + 21:'Double curve', + 22:'Bumpy road', + 23:'Slippery road', + 24:'Road narrows on the right', + 25:'Road work', + 26:'Traffic signals', + 27:'Pedestrians', + 28:'Children crossing', + 29:'Bicycles crossing', + 30:'Beware of ice/snow', + 31:'Wild animals crossing', + 32:'End speed + passing limits', + 33:'Turn right ahead', + 34:'Turn left ahead', + 35:'Ahead only', + 36:'Go straight or right', + 37:'Go straight or left', + 38:'Keep right', + 39:'Keep left', + 40:'Roundabout mandatory', + 41:'End of no passing', + 42:'End no passing veh > 3.5 tons' } + + +#D:\mine_\code files @@\pythonf\traffic_proj + +from keras.models import load_model + +# Load the model +loaded_model = load_model('D:/mine_/code files @@/pythonf/traffic_proj/modelh.h5') + + +# Load the pre-trained model +# loaded_model = pickle.load(open('D:/mine_/code files @@/pythonf/traffic_proj/sign_model.sav', 'rb')) + +# import joblib + +# # Load the model +# loaded_model = joblib.load('D:/mine_/code files @@/pythonf/traffic_proj/modelh.h5') + + +# Function to make predictions +def predict_traffic_sign(image): + # Preprocess the image + image = image.resize((30, 30)) + image = np.array(image) + image = np.expand_dims(image, axis=0) + # Predict using the loaded model + prediction = np.argmax(loaded_model.predict(image)) + return classes[prediction] + +# Function to convert text to audio and embed it in HTML +def text_to_audio(text, language='en'): + # Generate audio from text + tts = gTTS(text=text, lang=language, slow=False) + # Save audio as a temporary file + audio_path = "prediction_audio.mp3" + tts.save(audio_path) + # Create HTML audio player with autoplay + audio_html = f'' + return audio_html + + +def main(): + st.title("Traffic Sign Recognition App") + + st.write("Upload an image of a traffic sign to predict its class.") + + # File uploader + uploaded_file = st.file_uploader("upload your image here......", type=["jpg", "jpeg", "png"]) + + if uploaded_file is not None: + # Display the image + image = Image.open(uploaded_file) + st.image(image, caption='Uploaded Image', width=400) + + # Make prediction + prediction = predict_traffic_sign(image) + st.write("Prediction:", prediction) + + # audio_path = "D:/mine_/code files @@/pythonf/traffic_proj/outputaudio.mp3" + + # # Display the audio player + # st.audio(audio_path, format='audio/mp3') + + # Example usage + # Replace this with your prediction value + st.write("Prediction:", prediction) + + # Convert prediction text to audio and display it + audio_html = text_to_audio(prediction) + st.write(HTML(audio_html)) + + + +if __name__ == '__main__': + main() diff --git a/modelh.h5 b/modelh.h5 new file mode 100644 index 0000000000000000000000000000000000000000..53a14ab5ebeefac1626f95936e01e881d3b99374 GIT binary patch literal 2966232 zcmeFZ2Ut`)(>T5~L5k8uumA!oO7F0n98^#c0YPaNM7k(VstrX!DK_^%&SWx~OeT|L)9h`>$w&^6Wbqye z36>~Jw)<7^?;HPVAEVb@B*+WkGx;w<{4|xHmI(K}2(fyxcraytxh$W)x=2rf3;#p6 zNn^*d7)$|uLCXJ(#nSG16VUly{@2TYgaquzj&|WS)QjI*Lw?%C*E4>W6&4W?80r%r z7!o`yCYmXXh>Qsd3t12t^+OpCSD>$awGw>(hg6QQuRrUxG|RplSBTYzrO1+C%?XV1 zjrNHPjEWA42xlNFLPFhN@IMigg*< zo$i6lr^6G)Z+yvg)9I0ie?)jtNHDJg6^0oePk+W&t^xz()8h@%-{{G9(~F7n4G9kk z5BA}c{Co5Qc}(%?i88N3EV1tP3dXU(9@vjyfXq|(J9{AVr}jX*#~iT)dhmhj+x@*j zKSnwCbf#elSG~HT*+;qoaMoeZvAZ*y03rH!2%*07 z8B@w2O#7M8`0&Ws7)KuXCqjO{G5)iBLU>@G=vlszylSU~$A*ULs+$<{|Gb&H17hZP z!!#J?ePc|Fd1Rs^eWRjz9|ZY^Mh7wlQNF>!fdM}h2-xiDubyf&5)yQo7W}@UHoOkC z{fW2Vf6W7S+fiS?P+p}mQL(%_f5q58+NhwA(3l>9nHV#qnAs?tnFgboiH|1*GhKBv zUelvvqCx@!yTxjxt8TF8WO8OWiIsA}S)rJv@ZRb~m_t z#_OgO9oXHIJXK)&i{T_VB$^RcV1Ph51rQ!zOwayT_?Q|P716`q_xk^Ko&44_OvQ%! zM)6zUqqQ2{{QMHqE!&Wo`98md@@X=v%5*q0UGsYJN0NU4{EK?*W5kp6Kd8xnY3N@X z`dtnGTQta^3A}HCXumE z|H2&R(>-tggB<-f_RUQhmiWCdn4L_R$(bkLA7m+*Q2v^odWH;d4*6?#`oW$22fQpF zlYeP;`b$Iq@}GLV=Rdefft zkT>^Fc~9R*%fIT**$VXWSMDVb_D>C7fwr15e%nvV8XXZ7!?@hMVe!{GzbEh|h%Njd z(O2(;gr0aEFBZ>xy5sXqx=Bk3SR5h-Sie%o=1quUEqY znFx|U4{h2X0&`A*zTr;YaL*{;$jCp$=LE*t*WW)j%GbY}-mgMlLE%4h@%@X01aIC# zp=Wo8iQoLj4u4(4YlC2;hoQnR{cR8EhXL^W_>oO)bWB7TH9EleXYWVAwgA*qxlcf# zzwi9ts_+jDi45n3p1xNa92()rli(i!yb>nV7R!sA@fqX|mcTGyra%yXWO6=X5n+tz zV|g?U^{uR!hVx1zm_4TWsF0XIpP;DjkSQa{?}TQD#4sB(VUZy}#uY=D$X#GCBXOVa zg7~4P&_Lg)?hT#qX2#Ia$gt-zwJ^1^Ff}vcjdZ_2CMams!;2tm%xA5ex5(&_&H1dAjFd=2bvPkP7G-^YH}nYyrLQ@0i-8`0(%LJgzpXeD0_6xfA2^qYedRQzuemw%de~!b;^WlQ;1o3;` zwjS>h@Xs(iShKl%FgoeecUT+nWwnK1}6;5Yj>cGZ7{7xzcJA$&YRfBZ~O(BT@t!ux@q z08f*TC+L4Zy`ROv()tx%oWURPhVtHSVFztQ`Sr^Cnlb$@&xJ}li|;eGFq-|+a`-rx5% z`TYH1nDDpzevkK^-fzRn;8*p2*T3(>^7}sf@7nPLJwby7c3NOhy7?2}{V=Ws_V?F% z|69kI@cH{4o`BvD9cTKhb_no(Qv;S6AMbbk3EKMuf9AiU_Z{!MTCptnc!K$YnV6Z0 zl-V5XwyJy}lN1UzP=71>>+LTI{M#ik*?FR^5VN~4@INB?3j@J9fQ|foHQ%8SjKdF0 zduBudUh2diPo~6G;L-fsoA$rTfZ%+|&+?LHNpy=yi18d18Ef2qu%Ub7Il7y_KRrLi zoFC&o0>4C%c6S56vv@v5_bWfolYF;-$ItV6sM~+#=Xo~jM|>X5AM?C#yL*q1&-10b z{bqiiSND(fc<*4uyznx3_v-5X7e`4dazIEB0^awj}tDo)^Dd;P2N>>yeVcPCn%4 zC1&)LtMi4}`_dk&Jnw5mDunwYx@4`!iF786_GIal}FI-%_3J$zZ#>>Av=NyXLg&Hqb!i2_7 z{48@CT3u9Fqps$T4vjcKTEbS4_rp7h21yu(FqTOx`R_Vnd@_)e+8R6HCzRxs)wSu`lHaEGYb|s zj^P?Fl7fIG!dNA23rF2+09^3OhShVFK}2gS$jmDM%J&_}w)G<(S{q=OcnSDM7sKth z25{@4IdLm-g7Yu(KwGvAJ|CTg<*Ryubc--Ocl99pb(l7MR=Yy7vkb7wyozgmhjBG>j~n{i zHV278X&Q8fXQP4Qdr@?MBXE8-kfc%r;r`=7vQhLP)bGDd?gYFeB@1d`#+`R$W0f!z zdYppN!vv|F%>%KT-cUGvGgN>0LZ)){kg$gIR2dKD!@EcdZ2}Cns33c`&)-bCf8o z$>(Tz@5AR7Z{kYjx8Y4D=i%K-MLbe=8oU@Of~P+l0d4EIf|JlT6tazx<|M4*k_dadOySi8U1&Pas(BZf0nO(uNyhO6$Xk<+s~Ycdyr!S!R!f;c z{Ep>tNGl%}-Iay@*Guu8#$?E@aG_J}UqI$S9j-ypT9S#R31?L>Y}qXg=if-8&>bRB ztzm*a6j_`>yZ7O!18llV#SETL8igIM8p9jw1`x^9r=JTSB^M91!Z=?MqA@26G(`@9 zg`6@>E9lROx5$IfC5up^*bYu~OfxL#yBUtQh}Y~6Gpd<=#FHK+MscPzSHPF}2V@hg z2qoS)OF{<4Xu%_!`7?gPsT*(C5xN0?&S*$}_ADQDh`**@_ zp|M!m?momToknZ7w4wA@5@0`V8j`Fg(6Tl0aAx2+kXOEqPUH^6o-I?k!p51fEsllf zJ>AT9e*?tn>}5D|Hh_G}Hig3=N{btxA*%7x5O30fd^%I%ZE7xe*`2vCbg?h=b`Yg$ z*()TSm5C(gKEuZg%8-8aOq%Yhf-9N3$+)ZQppP=bB26{03#-xJK(X$H;JT#j6tJZxjn!WoAn0MfPSWcw$?VcjywT{IFp-xosI@Gee*`)o)z z+f}_Ruou=EB@f;@QgrM^9gy_bCF^tNU~Z=fHjExbJ2Xp^L1aEY{2>_b&SBvV%DLof zO&}O{+L4{c4`J)I{v<%%1R@^-Nc&B|nHL{J?>H&E);A35byjc;PHR9*pdUW5VF!5{ zv<@DxY9q}tB4Ar%0m8i{uyKSfp3|&CSHuw*GU+ zaU@*U&LK}Otb$@QHur_67Z|NO##t|?K%ZIO1PPgbpgzV38l4MBj@(3i?rJu)WM2aF zRr%!I{fW5gn>C5G^C8f814{7gh0Q+q2kZ3+HQvdB7aEVq_jV@zF9xg2FQ9+G7owV{%TZJ~$nhq_@xybPAiSZHttMN6ruN$f z64NrU>DN-!?zay`wl<)MVrNvP*hVg_SEC0iZh^fyl_09W8cNFgLDGX)H7njFl7Qpl z;OO88EoH|cXUJS*AZZ=~rv z3rxAEqnn{}p(y&Qa|V5pc?a#*1@NZ2p3V9s3)i>vCggy>NG^4HPzls=0Di7YVoC1Wnl$;1w

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