Create app.py

app.py

@@ -0,0 +1,43 @@
+from detecto import core, utils, visualize
+from detecto.visualize import show_labeled_image, plot_prediction_grid
+from torchvision import transforms
+import matplotlib.pyplot as plt
+from tensorflow.keras.utils import img_to_array
+import numpy as np
+import warnings
+import streamlit as st
+warnings.filterwarnings("ignore", category=UserWarning) 
+
+
+
+
+MODEL_PATH = "SD_model_weights.pth"
+IMAGE_PATH = "img1.jpeg"
+model = core.Model.load(MODEL_PATH, ['cross_arm','pole','tag'])
+#warnings.warn(msg)
+
+st.title("Object Detection")
+
+
+def detect_object(IMAGE_PATH)
+    image = utils.read_image(IMAGE_PATH) 
+    predictions = model.predict(image)
+    labels, boxes, scores = predictions
+
+
+    thresh=0.2
+    filtered_indices=np.where(scores>thresh)
+    filtered_scores=scores[filtered_indices]
+    filtered_boxes=boxes[filtered_indices]
+    num_list = filtered_indices[0].tolist()
+    filtered_labels = [labels[i] for i in num_list]
+    visualize.show_labeled_image(image, filtered_boxes, filtered_labels)
+    #img_array = img_to_array(img)
+
+  
+    
+    
+
+
+
+