Create app.py

app.py

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+import os
+import numpy as np
+import streamlit as st
+import matplotlib.pyplot as plt
+
+from sentinelhub import (
+    SHConfig,
+    SentinelHubRequest,
+    DataCollection,
+    MimeType,
+    BBox,
+    CRS,
+    bbox_to_dimensions,
+)
+
+st.set_page_config(page_title="Sentinel-2 NDWI (B8A-B11 / B8A-B12)", layout="wide")
+
+st.title("Sentinel-2 NDWI (agri) + détection de stress hydrique")
+st.caption("NDWI agri: (B8A − SWIR) / (B8A + SWIR), avec SWIR = B11 (1610 nm) ou B12 (2200 nm)")
+
+# ----------------------------
+# Secrets / config
+# ----------------------------
+def make_sh_config() -> SHConfig:
+    cfg = SHConfig()
+    # Deux façons: secrets Streamlit (HF Spaces) ou variables d'env
+    # Mets au moins SH_CLIENT_ID et SH_CLIENT_SECRET.
+    cfg.sh_client_id = st.secrets.get("SH_CLIENT_ID", os.getenv("SH_CLIENT_ID", ""))
+    cfg.sh_client_secret = st.secrets.get("SH_CLIENT_SECRET", os.getenv("SH_CLIENT_SECRET", ""))
+
+    # Si tu utilises un endpoint spécifique, tu peux aussi le mettre en secret/env
+    # cfg.sh_base_url = st.secrets.get("SH_BASE_URL", os.getenv("SH_BASE_URL", cfg.sh_base_url))
+
+    if not cfg.sh_client_id or not cfg.sh_client_secret:
+        st.error(
+            "Identifiants Sentinel Hub manquants. Ajoute SH_CLIENT_ID et SH_CLIENT_SECRET dans Settings → Secrets (HF Space)."
+        )
+        st.stop()
+
+    return cfg
+
+config = make_sh_config()
+
+# ----------------------------
+# UI inputs
+# ----------------------------
+with st.sidebar:
+    st.header("Zone (BBox WGS84)")
+    st.write("Entrez les coordonnées en **lon/lat** (EPSG:4326).")
+    col1, col2 = st.columns(2)
+    with col1:
+        min_lon = st.number_input("min_lon", value=3.85, format="%.6f")
+        min_lat = st.number_input("min_lat", value=43.58, format="%.6f")
+    with col2:
+        max_lon = st.number_input("max_lon", value=3.95, format="%.6f")
+        max_lat = st.number_input("max_lat", value=43.64, format="%.6f")
+
+    st.divider()
+    st.header("Dates")
+    start_date = st.date_input("Début", value=None)
+    end_date = st.date_input("Fin", value=None)
+
+    st.divider()
+    st.header("Paramètres NDWI")
+    swir_choice = st.selectbox("Formule", ["B8A & B11 (1610 nm)", "B8A & B12 (2200 nm)"])
+    p = st.slider("Percentile p (stress = NDWI < pᵉ percentile)", min_value=1, max_value=49, value=15, step=1)
+
+    st.divider()
+    st.header("Résolution")
+    res_m = st.slider("Résolution (m/pixel) — approx", min_value=10, max_value=120, value=30, step=10)
+
+    st.divider()
+    run = st.button("🚀 Lancer", type="primary")
+
+# Defaults for dates if user left empty
+import datetime as dt
+today = dt.date.today()
+if start_date is None:
+    start_date = today - dt.timedelta(days=14)
+if end_date is None:
+    end_date = today
+
+if not (min_lon < max_lon and min_lat < max_lat):
+    st.error("BBox invalide: vérifie min < max.")
+    st.stop()
+
+time_interval = (start_date.isoformat(), end_date.isoformat())
+
+# ----------------------------
+# DataCollection
+# ----------------------------
+# SentinelHub DataCollection standard
+S2_L2A = DataCollection.SENTINEL2_L2A
+
+# ----------------------------
+# EvalScripts
+# ----------------------------
+evalscript_bands = """
+//VERSION=3
+function setup() {
+  return {
+    input: [{ bands: ["B8A", "B11", "B12", "dataMask"] }],
+    output: { bands: 4, sampleType: "FLOAT32" }
+  };
+}
+function evaluatePixel(s) { return [s.B8A, s.B11, s.B12, s.dataMask]; }
+"""
+
+evalscript_truecolor = """
+//VERSION=3
+function setup() {
+  return {
+    input: [{ bands: ["B04","B03","B02","dataMask"] }],
+    output: { bands: 4, sampleType: "FLOAT32" }
+  };
+}
+function evaluatePixel(s) { return [s.B04, s.B03, s.B02, s.dataMask]; }
+"""
+
+# ----------------------------
+# Helpers
+# ----------------------------
+def request_tiff(evalscript: str, bbox: BBox, size: tuple[int, int]):
+    req = SentinelHubRequest(
+        evalscript=evalscript,
+        input_data=[SentinelHubRequest.input_data(data_collection=S2_L2A, time_interval=time_interval)],
+        responses=[SentinelHubRequest.output_response("default", MimeType.TIFF)],
+        bbox=bbox,
+        size=size,
+        config=config,
+    )
+    return req.get_data()[0]
+
+def normalize_rgb(rgb):
+    # robust-ish normalization
+    mx = np.nanpercentile(rgb, 99)
+    if not np.isfinite(mx) or mx <= 0:
+        mx = np.nanmax(rgb)
+    if not np.isfinite(mx) or mx <= 0:
+        mx = 1.0
+    out = np.clip(rgb / mx, 0, 1)
+    return out
+
+# ----------------------------
+# Run
+# ----------------------------
+if not run:
+    st.info("Configure la zone + dates, puis clique **Lancer**.")
+    st.stop()
+
+with st.spinner("Téléchargement Sentinel-2 + calcul NDWI…"):
+    bbox = BBox(bbox=[min_lon, min_lat, max_lon, max_lat], crs=CRS.WGS84)
+
+    # On approx la taille via res_m (en mètres/pixel)
+    # SentinelHub fait le calcul via bbox_to_dimensions (distance géodésique approx en WGS84)
+    size = bbox_to_dimensions(bbox, resolution=res_m)
+
+    # cap to avoid huge images in Spaces
+    max_side = 1600
+    if max(size) > max_side:
+        scale = max_side / max(size)
+        size = (max(64, int(size[0] * scale)), max(64, int(size[1] * scale)))
+
+    bands = request_tiff(evalscript_bands, bbox, size)
+    tc = request_tiff(evalscript_truecolor, bbox, size)
+
+    b8a, b11, b12, m = bands[..., 0], bands[..., 1], bands[..., 2], bands[..., 3]
+    rgb = tc[..., :3]
+    mask_rgb = tc[..., 3]
+
+    # masks
+    b8a = np.where(m > 0, b8a, np.nan)
+    b11 = np.where(m > 0, b11, np.nan)
+    b12 = np.where(m > 0, b12, np.nan)
+
+    rgb = np.where(mask_rgb[..., None] > 0, rgb, np.nan)
+    rgb = normalize_rgb(rgb)
+
+    eps = 1e-6
+    ndwi_11 = (b8a - b11) / (b8a + b11 + eps)
+    ndwi_12 = (b8a - b12) / (b8a + b12 + eps)
+
+    ndwi_used = ndwi_11 if "B11" in swir_choice else ndwi_12
+
+    thr = np.nanpercentile(ndwi_used, p)
+    stress = (ndwi_used < thr).astype(float)
+    stress = np.where(np.isfinite(ndwi_used), stress, np.nan)
+
+# ----------------------------
+# Visualisations
+# ----------------------------
+left, right = st.columns([1.2, 1.0], gap="large")
+
+with left:
+    st.subheader("Overlay stress hydrique sur vraie couleur")
+    fig = plt.figure(figsize=(8, 8))
+    plt.imshow(rgb)
+    plt.imshow(stress, cmap="Reds", alpha=0.40, vmin=0, vmax=1)
+    plt.axis("off")
+    plt.title(f"Stress = NDWI < p{p} (seuil {thr:.3f}) — {swir_choice}")
+    st.pyplot(fig, clear_figure=True)
+
+with right:
+    st.subheader("Cartes NDWI")
+    fig2 = plt.figure(figsize=(9, 4))
+    ax1 = plt.subplot(1, 2, 1)
+    im1 = ax1.imshow(ndwi_11, cmap="viridis")
+    ax1.set_title("NDWI (B8A, B11)")
+    ax1.axis("off")
+
+    ax2 = plt.subplot(1, 2, 2)
+    im2 = ax2.imshow(ndwi_12, cmap="viridis")
+    ax2.set_title("NDWI (B8A, B12)")
+    ax2.axis("off")
+
+    st.pyplot(fig2, clear_figure=True)
+
+st.divider()
+st.write("**Détails**")
+st.write(
+    {
+        "time_interval": time_interval,
+        "bbox_wgs84": [min_lon, min_lat, max_lon, max_lat],
+        "size_px": list(size),
+        "resolution_m": res_m,
+        "p": p,
+        "threshold": float(thr),
+        "formula_used": swir_choice,
+    }
+)