Rename streamlit_app.py to app.py

app.py

@@ -0,0 +1,69 @@
+import streamlit as st
+import numpy as np
+import cv2
+import matplotlib.pyplot as plt
+from PIL import Image
+from pdf2image import convert_from_bytes
+import io
+
+st.title("📉 TGA Graph Interpreter")
+st.write("Upload a TGA plot (JPG, PNG, GIF, PDF) to extract key thermal analysis values.")
+
+# ---- File Upload ----
+uploaded_file = st.file_uploader("Upload TGA Graph", type=["jpg", "jpeg", "png", "gif", "pdf"])
+
+if uploaded_file:
+    # Handle PDF separately (convert to image)
+    if uploaded_file.type == "application/pdf":
+        images = convert_from_bytes(uploaded_file.read())
+        img = np.array(images[0])  # Take first page
+        img = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)
+    else:
+        file_bytes = np.asarray(bytearray(uploaded_file.read()), dtype=np.uint8)
+        img = cv2.imdecode(file_bytes, 1)
+
+    st.image(img, caption="Uploaded TGA Plot", use_column_width=True)
+
+    # ---- Image Processing (basic curve extraction) ----
+    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+    blur = cv2.GaussianBlur(gray, (5, 5), 0)
+    edges = cv2.Canny(blur, 50, 150)
+
+    # Find contours (assume largest is the TGA curve)
+    contours, _ = cv2.findContours(edges, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+    if contours:
+        largest_contour = max(contours, key=cv2.contourArea)
+        curve = largest_contour.squeeze()
+
+        if curve.ndim == 2:
+            x_vals = curve[:, 0]
+            y_vals = curve[:, 1]
+
+            # Normalize (assume X = Temp, Y = Weight%)
+            x_norm = np.interp(x_vals, (x_vals.min(), x_vals.max()), (25, 800))  # °C
+            y_norm = np.interp(y_vals, (y_vals.min(), y_vals.max()), (100, 0))   # %
+
+            # Key points
+            onset_temp = x_norm[np.argmax(np.gradient(y_norm) < -0.1)]
+            peak_degradation = x_norm[np.argmin(np.gradient(y_norm))]
+            weight_loss = y_norm[0] - y_norm[-1]
+
+            # ---- Show Results ----
+            st.subheader("🔑 Extracted Values")
+            st.write(f"**Onset Temperature:** {onset_temp:.1f} °C")
+            st.write(f"**Peak Degradation Temp:** {peak_degradation:.1f} °C")
+            st.write(f"**Total Weight Loss:** {weight_loss:.1f} %")
+
+            # ---- Plot Curve ----
+            fig, ax = plt.subplots()
+            ax.plot(x_norm, y_norm, label="TGA Curve", color="blue")
+            ax.axvline(onset_temp, color="green", linestyle="--", label="Onset")
+            ax.axvline(peak_degradation, color="red", linestyle="--", label="Peak Degradation")
+            ax.set_xlabel("Temperature (°C)")
+            ax.set_ylabel("Weight (%)")
+            ax.legend()
+            st.pyplot(fig)
+        else:
+            st.error("Curve extraction failed. Try uploading a clearer TGA image.")
+    else:
+        st.error("No TGA curve detected. Please try another image.")