Update app.py

app.py

@@ -1,69 +1,73 @@
 import streamlit as st
-import numpy as np
-import cv2
 import matplotlib.pyplot as plt
+import numpy as np
+from plotdigitizer import digitizer
 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.")
+# Utility functions
+def analyze_curve(x, y):
+    """Analyze onset, peak degradation, weight loss for a single thermogram"""
+    x, y = np.array(x), np.array(y)
+
+    # Normalize weight % if needed
+    if y.max() > 100:
+        y = 100 * y / y[0]
+
+    # Onset = first big drop
+    dy = np.gradient(y, x)
+    onset_idx = np.argmax(dy < -0.05)
+    onset_temp = x[onset_idx] if onset_idx > 0 else None
+
+    # Peak degradation = minimum derivative
+    peak_idx = np.argmin(dy)
+    peak_temp = x[peak_idx] if peak_idx > 0 else None
+
+    # Weight loss
+    weight_loss = y[0] - y[-1]
+
+    return onset_temp, peak_temp, weight_loss
+
+
+st.title("TGA Graph Interpreter (Multi-Curve Support)")
 
-# ---- File Upload ----
-uploaded_file = st.file_uploader("Upload TGA Graph", type=["jpg", "jpeg", "png", "gif", "pdf"])
+uploaded_file = st.file_uploader(
+    "Upload a TGA plot (PNG, JPG, PDF)", type=["png", "jpg", "jpeg", "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)
+    # Read image
+    img = Image.open(uploaded_file)
+    st.image(img, caption="Uploaded TGA Graph", use_column_width=True)
+
+    # Use plotdigitizer to extract data
+    st.info("Extracting curves... please wait")
+    with io.BytesIO() as buf:
+        img.save(buf, format="PNG")
+        buf.seek(0)
+        curves = digitizer.extract(buf)
+
+    if not curves:
+        st.error("No curves detected. Try uploading a clearer plot.")
     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 ----
+        st.success(f"{len(curves)} curves detected!")
+
+        for i, curve in enumerate(curves):
+            x, y = curve["x"], curve["y"]
+            label = curve.get("label", f"Curve {i+1}")
+
+            onset, peak, loss = analyze_curve(x, y)
+
+            st.subheader(f"Results for {label}")
+            st.write(f"- **Onset Temperature:** {onset:.2f} °C" if onset else "Not detected")
+            st.write(f"- **Peak Degradation Temperature:** {peak:.2f} °C" if peak else "Not detected")
+            st.write(f"- **Weight Loss:** {loss:.2f} %")
+
+            # Plot each 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.plot(x, y, label=label)
             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.")
+