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app.py

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+import streamlit as st
+from streamlit_webrtc import webrtc_streamer, VideoTransformerBase
+import av
+import cv2
+import numpy as np
+from PIL import Image
+from ultralytics import YOLO
+
+# Load the YOLO model
+model = YOLO("welding.pt")
+
+st.set_page_config(page_title="Welding Detection App", layout="centered")
+st.title("🖼️ Welding Detection App with YOLOv8")
+st.markdown("Upload an image or use live webcam feed for detection.")
+
+# -------- Image Upload Detection --------
+with st.expander("📸 Upload Image for Detection"):
+    uploaded_file = st.file_uploader("Upload an image", type=["jpg", "jpeg", "png", "bmp", "tif", "tiff"])
+    if uploaded_file is not None:
+        image = Image.open(uploaded_file).convert("RGB")
+        image_np = np.array(image)
+        image_cv = cv2.cvtColor(image_np, cv2.COLOR_RGB2BGR)
+
+        st.image(image, caption="Uploaded Image", use_column_width=True)
+
+        if st.button("🔍 Run Detection"):
+            with st.spinner("Detecting..."):
+                results = model(image_cv, verbose=False)
+                detected = results[0].plot()
+                detected_rgb = cv2.cvtColor(detected, cv2.COLOR_BGR2RGB)
+                st.image(detected_rgb, caption="Detected Image", use_column_width=True)
+                st.success("Detection Complete ✅")
+
+# -------- Live Camera Detection --------
+st.markdown("---")
+st.subheader("🎥 Live Webcam Detection")
+
+class YOLOVideoTransformer(VideoTransformerBase):
+    def transform(self, frame: av.VideoFrame) -> np.ndarray:
+        image = frame.to_ndarray(format="bgr24")
+        results = model(image, verbose=False)
+        annotated_frame = results[0].plot()
+        return annotated_frame
+
+webrtc_streamer(
+    key="live",
+    video_processor_factory=YOLOVideoTransformer,
+    media_stream_constraints={"video": True, "audio": False},
+    async_processing=True,
+)

requirements.txt

@@ -1,3 +1,6 @@
-altair
-pandas
-streamlit
+streamlit
+gradio
+opencv-python
+torch
+ultralytics
+pillow

welding.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:761f6bcf0c19832068f485013d3ff80eb74615f99eab86f588ae8f2c22175989
+size 5478419