Update app.py

app.py

@@ -1,4 +1,3 @@
-
 import streamlit as st
 import numpy as np
 import matplotlib.pyplot as plt
@@ -26,44 +25,44 @@ tokenizer, model = load_model()
 class PressureSensor:
     def __init__(self, sensitivity=1.0):
         self.sensitivity = sensitivity
-    
+
     def measure(self, pressure):
         return pressure * self.sensitivity
 
 class TemperatureSensor:
     def __init__(self, base_temp=37.0):
         self.base_temp = base_temp
-    
+
     def measure(self, touch_temp):
         return self.base_temp + (touch_temp - self.base_temp) * 0.1
 
 class TextureSensor:
     def __init__(self):
         self.textures = ["smooth", "rough", "bumpy", "silky", "grainy"]
-    
+
     def measure(self, x, y):
         return self.textures[hash((x, y)) % len(self.textures)]
 
 class EMFieldSensor:
     def measure(self, x, y):
-        return np.sin(x/50) * np.cos(y/50) * 10  # simulated EM field
+        return np.sin(x / 50) * np.cos(y / 50) * 10  # simulated EM field
 
 # Create sensation map for the avatar
 def create_sensation_map(width, height):
     sensation_map = np.zeros((height, width, 7))  # RGBPVTE channels for pain, pleasure, neutral, pressure, velocity, temperature, and EM sensitivity
     for y in range(height):
         for x in range(width):
-            pain = np.exp(-((x-100)**2 + (y-150)**2) / 5000) + np.exp(-((x-300)**2 + (y-450)**2) / 5000)
-            pleasure = np.exp(-((x-200)**2 + (y-300)**2) / 5000) + np.exp(-((x-100)**2 + (y-500)**2) / 5000)
+            pain = np.exp(-((x - 100) ** 2 + (y - 150) ** 2) / 5000) + np.exp(-((x - 300) ** 2 + (y - 450) ** 2) / 5000)
+            pleasure = np.exp(-((x - 200) ** 2 + (y - 300) ** 2) / 5000) + np.exp(-((x - 100) ** 2 + (y - 500) ** 2) / 5000)
             neutral = 1 - (pain + pleasure)
-            pressure = np.exp(-((x-50)**2 + (y-150)**2) / 2000) + np.exp(-((x-350)**2 + (y-150)**2) / 2000) + \
-                       np.exp(-((x-100)**2 + (y-550)**2) / 2000) + np.exp(-((x-300)**2 + (y-550)**2) / 2000)
-            velocity = np.exp(-((x-200)**2 + (y-100)**2) / 5000) + np.exp(-((x-200)**2 + (y-300)**2) / 5000)
-            temperature = np.exp(-((x-200)**2 + (y-200)**2) / 10000)  # more sensitive in the core
-            em_sensitivity = np.exp(-((x-200)**2 + (y-100)**2) / 8000)  # more sensitive in the head
-            
+            pressure = np.exp(-((x - 50) ** 2 + (y - 150) ** 2) / 2000) + np.exp(-((x - 350) ** 2 + (y - 150) ** 2) / 2000) + \
+                       np.exp(-((x - 100) ** 2 + (y - 550) ** 2) / 2000) + np.exp(-((x - 300) ** 2 + (y - 550) ** 2) / 2000)
+            velocity = np.exp(-((x - 200) ** 2 + (y - 100) ** 2) / 5000) + np.exp(-((x - 200) ** 2 + (y - 300) ** 2) / 5000)
+            temperature = np.exp(-((x - 200) ** 2 + (y - 200) ** 2) / 10000)  # more sensitive in the core
+            em_sensitivity = np.exp(-((x - 200) ** 2 + (y - 100) ** 2) / 8000)  # more sensitive in the head
+
             sensation_map[y, x] = [pain, pleasure, neutral, pressure, velocity, temperature, em_sensitivity]
-    
+
     return sensation_map
 
 avatar_sensation_map = create_sensation_map(AVATAR_WIDTH, AVATAR_HEIGHT)
@@ -78,21 +77,21 @@ em_sensor = EMFieldSensor()
 def create_avatar():
     img = Image.new('RGB', (AVATAR_WIDTH, AVATAR_HEIGHT), color='white')
     draw = ImageDraw.Draw(img)
-    
+
     # Head
     draw.ellipse([150, 50, 250, 150], fill='beige', outline='black')
-    
+
     # Body
     draw.rectangle([175, 150, 225, 400], fill='beige', outline='black')
-    
+
     # Arms
     draw.rectangle([125, 150, 175, 350], fill='beige', outline='black')
     draw.rectangle([225, 150, 275, 350], fill='beige', outline='black')
-    
+
     # Legs
     draw.rectangle([175, 400, 200, 550], fill='beige', outline='black')
     draw.rectangle([200, 400, 225, 550], fill='beige', outline='black')
-    
+
     return img
 
 avatar_image = create_avatar()
@@ -127,16 +126,16 @@ with col2:
 def calculate_sensation(x, y, pressure, velocity):
     sensation = avatar_sensation_map[int(y), int(x)]
     pain, pleasure, neutral, pressure_sensitivity, velocity_sensitivity, temp_sensitivity, em_sensitivity = sensation
-    
+
     measured_pressure = pressure_sensor.measure(pressure * pressure_sensitivity)
     measured_temp = temp_sensor.measure(37 + pressure * 5)  # Simulating temperature increase with pressure
     measured_texture = texture_sensor.measure(x, y)
     measured_em = em_sensor.measure(x, y) * em_sensitivity
-    
+
     modified_pain = pain * measured_pressure / 10
     modified_pleasure = pleasure * velocity * velocity_sensitivity
     modified_neutral = neutral * (1 - (measured_pressure + velocity) / 2)
-    
+
     return modified_pain, modified_pleasure, modified_neutral, measured_pressure, measured_temp, measured_texture, measured_em
 
 def generate_description(x, y, pressure, velocity, pain, pleasure, neutral, measured_pressure, measured_temp, measured_texture, measured_em):
@@ -148,11 +147,11 @@ def generate_description(x, y, pressure, velocity, pain, pleasure, neutral, meas
     Resulting in:
     Pain: {pain:.2f}, Pleasure: {pleasure:.2f}, Neutral: {neutral:.2f}
     Avatar:"""
-    
+
     input_ids = tokenizer.encode(prompt, return_tensors="pt")
     output = model.generate(input_ids, max_length=200, num_return_sequences=1, no_repeat_ngram_size=2, top_k=50, top_p=0.95, temperature=0.7)
-    
- return tokenizer.decode(output[0], skip_special_tokens=True).split("Avatar: ")[-1].strip()
+
+    return tokenizer.decode(output[0], skip_special_tokens=True).split("Avatar: ")[-1].strip()
 
 # Initialize session state
 if 'touch_history' not in st.session_state:
@@ -165,23 +164,24 @@ if canvas_result.json_data is not None:
         new_points = objects[-1].get("points", [])
         if new_points:
             for i in range(1, len(new_points)):
-                x1, y1 = new_points[i-1]["x"], new_points[i-1]["y"]
+                x1, y1 = new_points[i - 1]["x"], new_points[i - 1]["y"]
                 x2, y2 = new_points[i]["x"], new_points[i]["y"]
-                
+
                 # Calculate pressure and velocity
-                distance = np.sqrt((x2-x1)**2 + (y2-y1)**2)
+                distance = np.sqrt((x2 - x1) ** 2 + (y2 - y1) ** 2)
                 velocity = distance / 0.01  # Assuming 10ms between points
                 pressure = 1 + velocity / 100  # Simple pressure model
-                
+
                 x, y = (x1 + x2) / 2, (y1 + y2) / 2
                 pain, pleasure, neutral, measured_pressure, measured_temp, measured_texture, measured_em = calculate_sensation(x, y, pressure, velocity)
-                
+
                 st.session_state.touch_history.append((x, y, pressure, velocity, pain, pleasure, neutral, measured_pressure, measured_temp, measured_texture, measured_em))
 
 # Display touch history and generate descriptions
 if st.session_state.touch_history:
     st.subheader("Touch History and Sensations")
-    for x, y, pressure, velocity, pain, pleasure, neutral, measured_pressure, measured_temp, measured_texture, measured_em in st.session_state.touch_history[-5:]:
+    for x, y, pressure, velocity, pain, pleasure, neutral, measured_pressure, measured_temp, measured_texture, measured_em in
+    st.session_state.touch_history[-5:]:
         st.write(f"Touch at ({x:.1f}, {y:.1f})")
         st.write(f"Pressure: {measured_pressure:.2f}, Temperature: {measured_temp:.2f}°C")
         st.write(f"Texture: {measured_texture}, EM Field: {measured_em:.2f}")
@@ -196,4 +196,4 @@ st.write("Draw on the avatar to simulate touch. The simulation will process pres
 # Add a button to clear the touch history
 if st.button("Clear Touch History"):
     st.session_state.touch_history = []
-    st.experimental_rerun()
+    st.experimental_rerun()