use the model

requirements.txt

@@ -1,5 +1,6 @@
 gradio
 numpy
 matplotlib
+tensorflow
 huggingface_hub
 

utils/color_model.py

@@ -1,60 +1,55 @@
-import json
 import numpy as np
+import tensorflow as tf
 from huggingface_hub import hf_hub_download
 
-# Download weights
-weights_path = hf_hub_download(
+# Download .h5 model from HF
+model_path = hf_hub_download(
     repo_id="danielritchie/vibe-color-model",
-    filename="vibe_weights.json"
+    filename="vibe_model.h5"
 )
 
-with open(weights_path, "r") as f:
-    weights = json.load(f)
-
-# Extract layers
-W0 = np.array(weights["layer_0"]["weights"], dtype=np.float32)
-b0 = np.array(weights["layer_0"]["biases"], dtype=np.float32)
-
-W1 = np.array(weights["layer_1"]["weights"], dtype=np.float32)
-b1 = np.array(weights["layer_1"]["biases"], dtype=np.float32)
-
-W2 = np.array(weights["layer_2"]["weights"], dtype=np.float32)
-b2 = np.array(weights["layer_2"]["biases"], dtype=np.float32)
-
-
-def relu(x):
-    return np.maximum(0, x)
-
-
-def sigmoid(x):
-    return 1 / (1 + np.exp(-x))
-
+# Load Keras model
+model = tf.keras.models.load_model(model_path)
 
 def infer_color(vad):
-    x = np.array([
+    input_data = np.array([[
         vad["V"],
         vad["A"],
         vad["D"],
         vad["Cx"],
         vad["Co"]
-    ], dtype=np.float32)
-
-    # Layer 0
-    x = relu(np.dot(x, W0) + b0)
+    ]], dtype=np.float32)
 
-    # Layer 1
-    x = relu(np.dot(x, W1) + b1)
+    output = model.predict(input_data, verbose=0)[0]
 
-    # Layer 2
-    x = sigmoid(np.dot(x, W2) + b2)
+    r, g, b, e, i = output
 
-    r, g, b, e, i = x.tolist()
+    return {
+        "R": float(r),
+        "G": float(g),
+        "B": float(b),
+        "E": float(e),
+        "I": float(i)
+    }
 
+def scale_rgb(rgb):
     return {
-        "R": r,
-        "G": g,
-        "B": b,
-        "E": e,
-        "I": i
+        "R": int(max(0, min(255, rgb["R"] * 255))),
+        "G": int(max(0, min(255, rgb["G"] * 255))),
+        "B": int(max(0, min(255, rgb["B"] * 255))),
+        "E": rgb["E"],
+        "I": rgb["I"]
     }
 
+def render_color(rgb):
+    return f"""
+    <div style="
+        width:100%;
+        height:240px;
+        border-radius:18px;
+        background: rgb({rgb['R']},{rgb['G']},{rgb['B']});
+        box-shadow: 0px 6px 32px rgba(0,0,0,0.25);
+        transition: all 0.3s ease-in-out;
+    "></div>
+    """
+