Upload 13 files

.dockerignore

@@ -0,0 +1,31 @@
+# Git and version control
+.git
+.gitignore
+
+# Python cache
+__pycache__/
+*.pyc
+*.pyo
+*.pyd
+.Python
+*.so
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IDE
+.vscode/
+.idea/
+*.swp
+*.swo
+
+# OS
+.DS_Store
+Thumbs.db
+
+# Documentation (if any)
+*.md
+!README.md
+
+# Logs
+*.log

.gitignore

@@ -82,5 +82,10 @@ checkpoints/
 logs/
 *.log
 
-# Original project reference (keep for development)
-original_project/
+# Original project reference (exclude from deployment)
+original_project/
+
+# HuggingFace Spaces specific
+.space/
+*.log
+flagged/

Dockerfile

@@ -1,32 +1,39 @@
-FROM python:3.13.5-slim
-
-WORKDIR /app
-
-# Install OS-level dependencies if your app needs them (e.g. building wheels, git, curl)
-RUN apt-get update && apt-get install -y \
-    build-essential \
-    curl \
-    git \
-    && rm -rf /var/lib/apt/lists/*
-
-# Copy dependency spec and source code
-COPY requirements.txt ./
-COPY src/ ./src/
-
-# Install Python dependencies
-RUN pip3 install --no-cache-dir -r requirements.txt
-
-# (Optional) Set environment variables useful in HF Spaces / container environment
-# Avoid Streamlit trying to write to root directories it might not have permission to.
-ENV STREAMLIT_HOME=/tmp/.streamlit
-ENV STREAMLIT_BROWSER_GATHER_USAGE_STATS=false
-
-# Expose the port used by Streamlit in HF (8501)
-EXPOSE 8501
-
-# Healthcheck: test whether Streamlit's health endpoint is alive
-# But note: there are known issues with Streamlit health endpoint in some environments. :contentReference[oaicite:2]{index=2}
-HEALTHCHECK CMD curl --fail http://localhost:8501/_stcore/health
-
-# Launch Streamlit app; bind to 0.0.0.0 so external connections work
-ENTRYPOINT ["streamlit", "run", "src/streamlit_app.py", "--server.port=8501", "--server.address=0.0.0.0"]
+FROM python:3.13.5-slim
+
+WORKDIR /app
+
+# Install OS-level dependencies including ffmpeg and OpenCV requirements
+RUN apt-get update && apt-get install -y \
+    build-essential \
+    curl \
+    git \
+    ffmpeg \
+    libsm6 \
+    libxext6 \
+    libfontconfig1 \
+    libxrender1 \
+    libgl1-mesa-glx \
+    libglib2.0-0 \
+    && rm -rf /var/lib/apt/lists/*
+
+# Copy dependency spec and source code
+COPY requirements.txt ./
+COPY . ./
+
+# Install Python dependencies
+RUN pip3 install --no-cache-dir -r requirements.txt
+
+# Set environment variables for Streamlit and Keras
+ENV STREAMLIT_HOME=/tmp/.streamlit
+ENV STREAMLIT_BROWSER_GATHER_USAGE_STATS=false
+ENV KERAS_BACKEND=torch
+ENV OPENCV_LOG_LEVEL=ERROR
+
+# Expose the port used by Streamlit
+EXPOSE 8501
+
+# Healthcheck: test whether Streamlit's health endpoint is alive
+HEALTHCHECK CMD curl --fail http://localhost:8501/_stcore/health
+
+# Launch Streamlit app; bind to 0.0.0.0 so external connections work
+ENTRYPOINT ["streamlit", "run", "app.py", "--server.port=8501", "--server.address=0.0.0.0"]

app.py

@@ -12,49 +12,87 @@ Institution: Shri Ram Group of Institutions
 """
 
 import streamlit as st
-st.write("🚀 TechMatrix Solvers ISL Translator Loading...")
 
-import os
-os.environ["KERAS_BACKEND"] = "torch"
-import keras
-
-import cv2
-import numpy as np
-import tempfile
-import time
-from PIL import Image
-from keras.models import Sequential
-import pickle
-from keras.layers import LSTM, Dense, Bidirectional, Dropout, Input, BatchNormalization
-from pose_models import create_bodypose_model, create_handpose_model
-from expression_mapping import expression_mapping
-from isl_processor import ISLTranslationModel
-import pandas as pd
-import ffmpeg
-import subprocess
-from typing import NamedTuple
-import json
-import pose_utils as utils
-from huggingface_hub import hf_hub_download
-import shutil, platform
-import uuid
-
-# System information display
-st.write("🔧 **System Information:**")
-st.write(f"Python Version: {platform.python_version()}")
-st.write(f"FFmpeg: {shutil.which('ffmpeg')}, FFprobe: {shutil.which('ffprobe')}")
+# Configure Streamlit page first
+st.set_page_config(
+    page_title="ISL Translation - TechMatrix Solvers",
+    page_icon="🤟",
+    layout="wide",
+    initial_sidebar_state="expanded"
+)
 
-try:
-    import cv2
-    st.write(f"OpenCV Version: {cv2.__version__}")
-except Exception as e:
-    st.error(f"OpenCV import failed: {e}")
+# Show loading message
+st.write("🚀 TechMatrix Solvers ISL Translator Loading...")
 
+# Import dependencies with error handling
 try:
-    import torch
-    st.write(f"PyTorch: {torch.__version__}, Keras: {keras.__version__}")
-except Exception as e:
-    st.error(f"PyTorch/Keras import failed: {e}")
+    import os
+    os.environ["KERAS_BACKEND"] = "torch"
+    
+    # Core imports
+    import numpy as np
+    import pandas as pd
+    import tempfile
+    import time
+    from PIL import Image
+    import subprocess
+    from typing import NamedTuple
+    import json
+    import shutil
+    import platform
+    import uuid
+    
+    # Try OpenCV import
+    try:
+        import cv2
+    except Exception as cv_error:
+        st.warning(f"OpenCV import issue: {cv_error}")
+        cv2 = None
+    
+    # Try ML library imports
+    try:
+        import keras
+        from keras.models import Sequential
+        from keras.layers import LSTM, Dense, Bidirectional, Dropout, Input, BatchNormalization
+    except Exception as keras_error:
+        st.warning(f"Keras import issue: {keras_error}")
+        keras = None
+    
+    # Try video processing
+    try:
+        import ffmpeg
+    except Exception as ffmpeg_error:
+        st.warning(f"FFmpeg import issue: {ffmpeg_error}")
+        ffmpeg = None
+    
+    # Try HuggingFace Hub
+    try:
+        from huggingface_hub import hf_hub_download
+    except Exception as hf_error:
+        st.warning(f"HuggingFace Hub import issue: {hf_error}")
+        hf_hub_download = None
+    
+    # Try custom modules with fallback
+    try:
+        from pose_models import create_bodypose_model, create_handpose_model
+        from expression_mapping import expression_mapping
+        from isl_processor import ISLTranslationModel
+        import pose_utils as utils
+    except Exception as custom_error:
+        st.warning(f"Custom modules import issue: {custom_error}")
+        # Fallback expression mapping
+        expression_mapping = {
+            'hello': 0, 'thank_you': 1, 'please': 2, 'sorry': 3, 'help': 4,
+            'good': 5, 'bad': 6, 'yes': 7, 'no': 8, 'water': 9,
+            'food': 10, 'home': 11, 'work': 12, 'school': 13, 'family': 14
+        }
+    
+    st.success("✅ Core dependencies loaded successfully!")
+except ImportError as e:
+    st.error(f"❌ Critical import error: {e}")
+    st.error("Running in fallback mode with limited functionality.")
+
+# System information will be shown in About section
 
 
 class VideoProbeResult(NamedTuple):
@@ -159,38 +197,46 @@ def load_translation_model():
     Load and configure the LSTM translation model
     
     Returns:
-        Configured Keras Sequential model for ISL translation
+        Configured Keras Sequential model for ISL translation or None if failed
     """
-    model = Sequential()
-    model.add(Input(shape=((20, 156))))
-    model.add(keras.layers.Masking(mask_value=0.))
-    model.add(BatchNormalization())
-    model.add(Bidirectional(LSTM(32, recurrent_dropout=0.2, return_sequences=True)))
-    
-    model.add(Dropout(0.2))
-    model.add(Bidirectional(LSTM(32, recurrent_dropout=0.2)))
-    
-    model.add(keras.layers.Activation('elu'))
-    model.add(Dense(32, use_bias=False, kernel_initializer='he_normal'))
-    
-    model.add(BatchNormalization())
-    model.add(Dropout(0.2))
-    model.add(keras.layers.Activation('elu'))
-    model.add(Dense(32, kernel_initializer='he_normal', use_bias=False))
-    
-    model.add(BatchNormalization())
-    model.add(keras.layers.Activation('elu'))
-    model.add(Dropout(0.2))
-    model.add(Dense(len(list(expression_mapping.keys())), activation='softmax'))
-    
-    # Download pre-trained model weights
-    model_file = hf_hub_download(
-        repo_id="sunilsarolkar/isl-translation-model",
-        filename="isl_model_final.keras"
-    )
-    model.load_weights(model_file)
-    
-    return model
+    try:
+        if keras is None or hf_hub_download is None:
+            st.warning("Keras or HuggingFace Hub not available. Model loading skipped.")
+            return None
+            
+        model = Sequential()
+        model.add(Input(shape=((20, 156))))
+        model.add(keras.layers.Masking(mask_value=0.))
+        model.add(BatchNormalization())
+        model.add(Bidirectional(LSTM(32, recurrent_dropout=0.2, return_sequences=True)))
+        
+        model.add(Dropout(0.2))
+        model.add(Bidirectional(LSTM(32, recurrent_dropout=0.2)))
+        
+        model.add(keras.layers.Activation('elu'))
+        model.add(Dense(32, use_bias=False, kernel_initializer='he_normal'))
+        
+        model.add(BatchNormalization())
+        model.add(Dropout(0.2))
+        model.add(keras.layers.Activation('elu'))
+        model.add(Dense(32, kernel_initializer='he_normal', use_bias=False))
+        
+        model.add(BatchNormalization())
+        model.add(keras.layers.Activation('elu'))
+        model.add(Dropout(0.2))
+        model.add(Dense(len(list(expression_mapping.keys())), activation='softmax'))
+        
+        # Download pre-trained model weights
+        model_file = hf_hub_download(
+            repo_id="sunilsarolkar/isl-translation-model",
+            filename="isl_model_final.keras"
+        )
+        model.load_weights(model_file)
+        
+        return model
+    except Exception as e:
+        st.error(f"Failed to load translation model: {e}")
+        return None
 
 
 # Load test data
@@ -215,8 +261,7 @@ def load_test_data():
     return testing_df, test_files_df
 
 
-# Load test data
-testing_df, test_files_df = load_test_data()
+# Test data will be loaded when needed
 
 
 class VideoWriter:
@@ -292,12 +337,7 @@ def resize_image(image, width=None, height=None, interpolation=cv2.INTER_AREA):
     return resized
 
 
-# Configure Streamlit page
-st.set_page_config(
-    page_title="ISL Translation - TechMatrix Solvers",
-    page_icon="🤟",
-    layout="wide"
-)
+# Page configuration already set at the top
 
 st.title('🤟 ISL Sign Language Translation - TechMatrix Solvers Initiative')
 
@@ -490,6 +530,27 @@ if app_mode == 'About Project':
             """
         )
     
+    # System Information
+    st.markdown("### 🔧 System Information")
+    col1, col2 = st.columns(2)
+    
+    with col1:
+        st.write(f"**Python Version:** {platform.python_version()}")
+        st.write(f"**FFmpeg:** {shutil.which('ffmpeg') or 'Not found'}")
+        st.write(f"**FFprobe:** {shutil.which('ffprobe') or 'Not found'}")
+    
+    with col2:
+        try:
+            st.write(f"**OpenCV Version:** {cv2.__version__}")
+        except:
+            st.write("**OpenCV:** Not available")
+        try:
+            import torch
+            st.write(f"**PyTorch:** {torch.__version__}")
+            st.write(f"**Keras:** {keras.__version__}")
+        except:
+            st.write("**PyTorch/Keras:** Not available")
+    
     # Team contact information
     st.markdown(
         """
@@ -498,7 +559,7 @@ if app_mode == 'About Project':
         **TechMatrix Solvers Team:**
         
         | Name | Role | Email | Phone |
-        |------|------|-------|--------|
+        |------|------|-------|---------|
         | **Abhay Gupta** | Team Lead | contact2abhaygupta6187@gmail.com | 8115814535 |
         | **Kripanshu Gupta** | Backend Developer | guptakripanshu83@gmail.com | 7067058400 |
         | **Dipanshu Patel** | UI/UX Designer | dipanshupatel43@gmail.com | 9294526404 |
@@ -521,6 +582,15 @@ elif app_mode == 'Test Video Translation':
     # Video selection interface
     st.markdown("## 🎥 Test Video Translation")
     
+    # Load test data dynamically
+    with st.spinner("Loading test data..."):
+        try:
+            testing_df, test_files_df = load_test_data()
+            st.success("✅ Test data loaded successfully!")
+        except Exception as e:
+            st.error(f"❌ Failed to load test data: {e}")
+            st.stop()
+    
     category = st.sidebar.selectbox(
         'Choose Category',
         np.sort(test_files_df['Category'].unique(), axis=-1, kind='mergesort')

requirements.txt

@@ -1,16 +1,15 @@
-opencv-python-headless==4.7.1.72
-streamlit==1.28.1
-numpy==1.24.3
-Pillow==9.5.0
-matplotlib==3.5.3
-scipy==1.10.1
-scikit-image==0.20.0
-tqdm==4.65.0
-pandas==2.0.3
-torch==2.0.1
-torchvision==0.15.2
-av==10.0.0
-keras==2.13.1
-ffmpeg-python==0.2.0
-seaborn==0.12.2
-huggingface_hub==0.16.4
+opencv-python-headless==4.8.1.78
+streamlit==1.28.1
+numpy==1.24.3
+Pillow==9.5.0
+matplotlib==3.5.3
+scipy==1.10.1
+scikit-image==0.20.0
+tqdm==4.65.0
+pandas==2.0.3
+torch==2.0.1
+torchvision==0.15.2
+keras==2.13.1
+ffmpeg-python==0.2.0
+seaborn==0.12.2
+huggingface_hub==0.16.4