Upload 3 files

app.py

@@ -4,7 +4,7 @@ from tensorflow.keras.models import load_model
 import numpy as np
 
 model=load_model("model.h5")
-st.title("Dog Breed Detection")
+st.title("Plant Seedlings Detection")
 img=st.camera_input("Camera")
 def process_image(input_img):
     if input_img.mode == 'RGBA':
@@ -19,4 +19,16 @@ if img is not None:
     image=process_image(img)
     prediction=model.predict(image)
     predicted_class=np.argmax(prediction)
-    st.write(predicted_class,"You can learn information about labels in Kaggle.")
+    class_names=["Black-grass",
+"Charlock",
+"Cleavers",
+"Common Chickweed",
+"Common wheat",
+"Fat Hen",
+"Loose Silky-bent",
+"Maize",
+"Scentless Mayweed",
+"Shepherds Purse",
+"Small-flowered Cranesbill",
+"Sugar beet"]
+    st.write(class_names[predicted_class])

model.h5

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:5164cee091e6162b687b699a1c969ad2fcce94561b58b943e6d09a7d87d519ca
-size 4873800
+oid sha256:718dfae95e4654cb18eaec536f14172da51ef690c007ad5fd71bdc57c6a4909b
+size 11556304

requirements.txt

@@ -1,4 +1,4 @@
 streamlit
-tensorflow
 pillow
+tensorflow
 numpy